paper_id stringlengths 15 35 | title stringlengths 26 182 | authors listlengths 1 25 | isca_url stringlengths 66 86 | pdf_url stringlengths 65 85 | doi stringlengths 27 30 | pages stringlengths 3 9 | bibtex large_stringlengths 294 850 | abstract large_stringlengths 247 1.59k | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
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|---|---|---|---|---|---|---|---|---|---|---|
huang21g_interspeech | Token-Level Supervised Contrastive Learning for Punctuation Restoration | [
"Qiushi Huang",
"Tom Ko",
"H. Lilian Tang",
"Xubo Liu",
"Bo Wu"
] | https://www.isca-archive.org/interspeech_2021/huang21g_interspeech.html | https://www.isca-archive.org/interspeech_2021/huang21g_interspeech.pdf | 10.21437/Interspeech.2021-661 | 2012-2016 | @inproceedings{huang21g_interspeech,
title = {{Token-Level Supervised Contrastive Learning for Punctuation Restoration}},
author = {Qiushi Huang and Tom Ko and H. Lilian Tang and Xubo Liu and Bo Wu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2012--2016},
doi = {10.21437... | Punctuation is critical in understanding natural language text. Currently,
most automatic speech recognition (ASR) systems do not generate punctuation,
which affects the performance of downstream tasks, such as intent detection
and slot filling. This gives rise to the need for punctuation restoration.
Recent work in pu... | 2107.09099 | title_snapshot |
zhao21_interspeech | BART Based Semantic Correction for Mandarin Automatic Speech Recognition System | [
"Yun Zhao",
"Xuerui Yang",
"Jinchao Wang",
"Yongyu Gao",
"Chao Yan",
"Yuanfu Zhou"
] | https://www.isca-archive.org/interspeech_2021/zhao21_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhao21_interspeech.pdf | 10.21437/Interspeech.2021-739 | 2017-2021 | @inproceedings{zhao21_interspeech,
title = {{BART Based Semantic Correction for Mandarin Automatic Speech Recognition System}},
author = {Yun Zhao and Xuerui Yang and Jinchao Wang and Yongyu Gao and Chao Yan and Yuanfu Zhou},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2017--2021... | Although automatic speech recognition (ASR) systems achieved significantly
improvements in recent years, spoken language recognition error occurs
which can be easily spotted by human beings. Various language modeling
techniques have been developed on post recognition tasks like semantic
correction. In this paper, we pr... | 2104.05507 | title_snapshot |
dai21b_interspeech | Class-Based Neural Network Language Model for Second-Pass Rescoring in ASR | [
"Lingfeng Dai",
"Qi Liu",
"Kai Yu"
] | https://www.isca-archive.org/interspeech_2021/dai21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/dai21b_interspeech.pdf | 10.21437/Interspeech.2021-1080 | 2022-2026 | @inproceedings{dai21b_interspeech,
title = {{Class-Based Neural Network Language Model for Second-Pass Rescoring in ASR}},
author = {Lingfeng Dai and Qi Liu and Kai Yu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2022--2026},
doi = {10.21437/Interspeech.2021-1080},
iss... | Language model rescoring, especially neural network language model
(NNLM) rescoring, is widely used to achieve improved performance in
a second-pass automatic speech recognition (ASR) system. The rescoring
NNLM is usually trained separately from the ASR system. Typically,
the two’s training corpora are different, leadi... | null | null |
kurata21_interspeech | Improving Customization of Neural Transducers by Mitigating Acoustic Mismatch of Synthesized Audio | [
"Gakuto Kurata",
"George Saon",
"Brian Kingsbury",
"David Haws",
"Zoltán Tüske"
] | https://www.isca-archive.org/interspeech_2021/kurata21_interspeech.html | https://www.isca-archive.org/interspeech_2021/kurata21_interspeech.pdf | 10.21437/Interspeech.2021-1656 | 2027-2031 | @inproceedings{kurata21_interspeech,
title = {{Improving Customization of Neural Transducers by Mitigating Acoustic Mismatch of Synthesized Audio}},
author = {Gakuto Kurata and George Saon and Brian Kingsbury and David Haws and Zoltán Tüske},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | Customization of automatic speech recognition (ASR) models using text
data from a target domain is essential to deploying ASR in various
domains. End-to-end (E2E) modeling for ASR has made remarkable progress,
but the advantage of E2E modeling, where all neural network parameters
are jointly optimized, is offset by the... | null | null |
saebi21_interspeech | A Discriminative Entity-Aware Language Model for Virtual Assistants | [
"Mandana Saebi",
"Ernest Pusateri",
"Aaksha Meghawat",
"Christophe Van Gysel"
] | https://www.isca-archive.org/interspeech_2021/saebi21_interspeech.html | https://www.isca-archive.org/interspeech_2021/saebi21_interspeech.pdf | 10.21437/Interspeech.2021-1767 | 2032-2036 | @inproceedings{saebi21_interspeech,
title = {{A Discriminative Entity-Aware Language Model for Virtual Assistants}},
author = {Mandana Saebi and Ernest Pusateri and Aaksha Meghawat and Christophe Van Gysel},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2032--2036},
doi = {... | High-quality automatic speech recognition (ASR) is essential for virtual
assistants (VAs) to work well. However, ASR often performs poorly on
VA requests containing named entities. In this work, we start from
the observation that many ASR errors on named entities are inconsistent
with real-world knowledge. We extend pr... | 2106.11292 | title_snapshot |
namazifar21_interspeech | Correcting Automated and Manual Speech Transcription Errors Using Warped Language Models | [
"Mahdi Namazifar",
"John Malik",
"Li Erran Li",
"Gokhan Tur",
"Dilek Hakkani Tür"
] | https://www.isca-archive.org/interspeech_2021/namazifar21_interspeech.html | https://www.isca-archive.org/interspeech_2021/namazifar21_interspeech.pdf | 10.21437/Interspeech.2021-591 | 2037-2041 | @inproceedings{namazifar21_interspeech,
title = {{Correcting Automated and Manual Speech Transcription Errors Using Warped Language Models}},
author = {Mahdi Namazifar and John Malik and Li Erran Li and Gokhan Tur and Dilek Hakkani Tür},
year = {2021},
booktitle = {{Interspeech 2021}},
pages =... | Masked language models have revolutionized natural language processing
systems in the past few years. A recently introduced generalization
of masked language models called warped language models are trained
to be more robust to the types of errors that appear in automatic or
manual transcriptions of spoken language by ... | 2103.14580 | title_snapshot |
shi21b_interspeech | Dynamic Encoder Transducer: A Flexible Solution for Trading Off Accuracy for Latency | [
"Yangyang Shi",
"Varun Nagaraja",
"Chunyang Wu",
"Jay Mahadeokar",
"Duc Le",
"Rohit Prabhavalkar",
"Alex Xiao",
"Ching-Feng Yeh",
"Julian Chan",
"Christian Fuegen",
"Ozlem Kalinli",
"Michael L. Seltzer"
] | https://www.isca-archive.org/interspeech_2021/shi21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/shi21b_interspeech.pdf | 10.21437/Interspeech.2021-1272 | 2042-2046 | @inproceedings{shi21b_interspeech,
title = {{Dynamic Encoder Transducer: A Flexible Solution for Trading Off Accuracy for Latency}},
author = {Yangyang Shi and Varun Nagaraja and Chunyang Wu and Jay Mahadeokar and Duc Le and Rohit Prabhavalkar and Alex Xiao and Ching-Feng Yeh and Julian Chan and Christian Fu... | We propose a dynamic encoder transducer (DET) for on-device speech
recognition. One DET model scales to multiple devices with different
computation capacities without retraining or finetuning. To trading
off accuracy and latency, DET assigns different encoders to decode
different parts of an utterance. We apply and com... | 2104.02176 | title_snapshot |
zhang21n_interspeech | Domain-Aware Self-Attention for Multi-Domain Neural Machine Translation | [
"Shiqi Zhang",
"Yan Liu",
"Deyi Xiong",
"Pei Zhang",
"Boxing Chen"
] | https://www.isca-archive.org/interspeech_2021/zhang21n_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhang21n_interspeech.pdf | 10.21437/Interspeech.2021-1477 | 2047-2051 | @inproceedings{zhang21n_interspeech,
title = {{Domain-Aware Self-Attention for Multi-Domain Neural Machine Translation}},
author = {Shiqi Zhang and Yan Liu and Deyi Xiong and Pei Zhang and Boxing Chen},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2047--2051},
doi = {10.21... | In this paper, we investigate multi-domain neural machine translation
(NMT) that translates sentences of different domains in a single model.
To this end, we propose a domain-aware self-attention mechanism that
jointly learns domain representations with the single NMT model. The
learned domain representations are integ... | null | null |
zeyer21_interspeech | Librispeech Transducer Model with Internal Language Model Prior Correction | [
"Albert Zeyer",
"André Merboldt",
"Wilfried Michel",
"Ralf Schlüter",
"Hermann Ney"
] | https://www.isca-archive.org/interspeech_2021/zeyer21_interspeech.html | https://www.isca-archive.org/interspeech_2021/zeyer21_interspeech.pdf | 10.21437/Interspeech.2021-1510 | 2052-2056 | @inproceedings{zeyer21_interspeech,
title = {{Librispeech Transducer Model with Internal Language Model Prior Correction}},
author = {Albert Zeyer and André Merboldt and Wilfried Michel and Ralf Schlüter and Hermann Ney},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2052--2056},
... | We present our transducer model on Librispeech. We study variants to
include an external language model (LM) with shallow fusion and subtract
an estimated internal LM. This is justified by a Bayesian interpretation
where the transducer model prior is given by the estimated internal
LM. The subtraction of the internal L... | 2104.03006 | title_snapshot |
mavandadi21_interspeech | A Deliberation-Based Joint Acoustic and Text Decoder | [
"Sepand Mavandadi",
"Tara N. Sainath",
"Ke Hu",
"Zelin Wu"
] | https://www.isca-archive.org/interspeech_2021/mavandadi21_interspeech.html | https://www.isca-archive.org/interspeech_2021/mavandadi21_interspeech.pdf | 10.21437/Interspeech.2021-165 | 2057-2061 | @inproceedings{mavandadi21_interspeech,
title = {{A Deliberation-Based Joint Acoustic and Text Decoder}},
author = {Sepand Mavandadi and Tara N. Sainath and Ke Hu and Zelin Wu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2057--2061},
doi = {10.21437/Interspeech.2021-165}... | We propose a new two-pass E2E speech recognition model that improves
ASR performance by training on a combination of paired data and unpaired
text data. Previously, the joint acoustic and text decoder (JATD) has
shown promising results through the use of text data during model training
and the recently introduced delib... | 2303.15293 | title_snapshot |
tuske21_interspeech | On the Limit of English Conversational Speech Recognition | [
"Zoltán Tüske",
"George Saon",
"Brian Kingsbury"
] | https://www.isca-archive.org/interspeech_2021/tuske21_interspeech.html | https://www.isca-archive.org/interspeech_2021/tuske21_interspeech.pdf | 10.21437/Interspeech.2021-211 | 2062-2066 | @inproceedings{tuske21_interspeech,
title = {{On the Limit of English Conversational Speech Recognition}},
author = {Zoltán Tüske and George Saon and Brian Kingsbury},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2062--2066},
doi = {10.21437/Interspeech.2021-211},
issn ... | In our previous work we demonstrated that a single headed attention
encoder-decoder model is able to reach state-of-the-art results in
conversational speech recognition. In this paper, we further improve
the results for both Switchboard 300 and 2000. Through use of an improved
optimizer, speaker vector embeddings, and ... | 2105.00982 | title_snapshot |
an21_interspeech | Deformable TDNN with Adaptive Receptive Fields for Speech Recognition | [
"Keyu An",
"Yi Zhang",
"Zhijian Ou"
] | https://www.isca-archive.org/interspeech_2021/an21_interspeech.html | https://www.isca-archive.org/interspeech_2021/an21_interspeech.pdf | 10.21437/Interspeech.2021-387 | 2067-2071 | @inproceedings{an21_interspeech,
title = {{Deformable TDNN with Adaptive Receptive Fields for Speech Recognition}},
author = {Keyu An and Yi Zhang and Zhijian Ou},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2067--2071},
doi = {10.21437/Interspeech.2021-387},
issn ... | Time Delay Neural Networks (TDNNs) are widely used in both DNN-HMM
based hybrid speech recognition systems and recent end-to-end systems.
Nevertheless, the receptive fields of TDNNs are limited and fixed,
which is not desirable for tasks like speech recognition, where the
temporal dynamics of speech are varied and affe... | 2104.14791 | title_snapshot |
you21_interspeech | SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts | [
"Zhao You",
"Shulin Feng",
"Dan Su",
"Dong Yu"
] | https://www.isca-archive.org/interspeech_2021/you21_interspeech.html | https://www.isca-archive.org/interspeech_2021/you21_interspeech.pdf | 10.21437/Interspeech.2021-478 | 2077-2081 | @inproceedings{you21_interspeech,
title = {{SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts}},
author = {Zhao You and Shulin Feng and Dan Su and Dong Yu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2077--2081},
doi = {10.21437/Interspe... | Recently, Mixture of Experts (MoE) based Transformer has shown promising
results in many domains. This is largely due to the following advantages
of this architecture: firstly, MoE based Transformer can increase model
capacity without computational cost increasing both at training and
inference time. Besides, MoE based... | 2105.03036 | title_snapshot |
leong21_interspeech | Online Compressive Transformer for End-to-End Speech Recognition | [
"Chi-Hang Leong",
"Yu-Han Huang",
"Jen-Tzung Chien"
] | https://www.isca-archive.org/interspeech_2021/leong21_interspeech.html | https://www.isca-archive.org/interspeech_2021/leong21_interspeech.pdf | 10.21437/Interspeech.2021-545 | 2082-2086 | @inproceedings{leong21_interspeech,
title = {{Online Compressive Transformer for End-to-End Speech Recognition}},
author = {Chi-Hang Leong and Yu-Han Huang and Jen-Tzung Chien},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2082--2086},
doi = {10.21437/Interspeech.2021-545}... | Traditionally, transformer with connectionist temporal classification
(CTC) was developed for offline speech recognition where the transcription
was generated after the whole utterance has been spoken. However, it
is crucial to carry out online transcription of speech signal for many
applications including live broadca... | null | null |
lin21e_interspeech | End to End Transformer-Based Contextual Speech Recognition Based on Pointer Network | [
"Binghuai Lin",
"Liyuan Wang"
] | https://www.isca-archive.org/interspeech_2021/lin21e_interspeech.html | https://www.isca-archive.org/interspeech_2021/lin21e_interspeech.pdf | 10.21437/Interspeech.2021-774 | 2087-2091 | @inproceedings{lin21e_interspeech,
title = {{End to End Transformer-Based Contextual Speech Recognition Based on Pointer Network}},
author = {Binghuai Lin and Liyuan Wang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2087--2091},
doi = {10.21437/Interspeech.2021-774},
i... | Most spoken language assessment systems rely on the text features extracted
from the automatic speech recognition (ASR) transcripts and thus depend
heavily on the accuracy of the ASR systems. Automatic speech scoring
tasks such as reading aloud and spontaneous speech are commonly provided
with the prompts in advance to... | null | null |
karita21_interspeech | A Comparative Study on Neural Architectures and Training Methods for Japanese Speech Recognition | [
"Shigeki Karita",
"Yotaro Kubo",
"Michiel Adriaan Unico Bacchiani",
"Llion Jones"
] | https://www.isca-archive.org/interspeech_2021/karita21_interspeech.html | https://www.isca-archive.org/interspeech_2021/karita21_interspeech.pdf | 10.21437/Interspeech.2021-775 | 2092-2096 | @inproceedings{karita21_interspeech,
title = {{A Comparative Study on Neural Architectures and Training Methods for Japanese Speech Recognition}},
author = {Shigeki Karita and Yotaro Kubo and Michiel Adriaan Unico Bacchiani and Llion Jones},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | End-to-end (E2E) modeling is advantageous for automatic speech recognition
(ASR) especially for Japanese since word-based tokenization of Japanese
is not trivial, and E2E modeling is able to model character sequences
directly. This paper focuses on the latest E2E modeling techniques,
and investigates their performances... | 2106.05111 | title_snapshot |
hori21b_interspeech | Advanced Long-Context End-to-End Speech Recognition Using Context-Expanded Transformers | [
"Takaaki Hori",
"Niko Moritz",
"Chiori Hori",
"Jonathan Le Roux"
] | https://www.isca-archive.org/interspeech_2021/hori21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/hori21b_interspeech.pdf | 10.21437/Interspeech.2021-1643 | 2097-2101 | @inproceedings{hori21b_interspeech,
title = {{Advanced Long-Context End-to-End Speech Recognition Using Context-Expanded Transformers}},
author = {Takaaki Hori and Niko Moritz and Chiori Hori and Jonathan Le Roux},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2097--2101},
doi ... | This paper addresses end-to-end automatic speech recognition (ASR)
for long audio recordings such as lecture and conversational speeches.
Most end-to-end ASR models are designed to recognize independent utterances,
but contextual information (e.g., speaker or topic) over multiple utterances
is known to be useful for AS... | 2104.09426 | title_snapshot |
haidar21_interspeech | Transformer-Based ASR Incorporating Time-Reduction Layer and Fine-Tuning with Self-Knowledge Distillation | [
"Md. Akmal Haidar",
"Chao Xing",
"Mehdi Rezagholizadeh"
] | https://www.isca-archive.org/interspeech_2021/haidar21_interspeech.html | https://www.isca-archive.org/interspeech_2021/haidar21_interspeech.pdf | 10.21437/Interspeech.2021-1743 | 2102-2106 | @inproceedings{haidar21_interspeech,
title = {{Transformer-Based ASR Incorporating Time-Reduction Layer and Fine-Tuning with Self-Knowledge Distillation}},
author = {Md. Akmal Haidar and Chao Xing and Mehdi Rezagholizadeh},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2102--2106},... | Reducing the input sequence length of speech features to alleviate
the complexity of alignment between speech features and text transcript
by sub-sampling approaches is an important way to get better results
in end-to-end (E2E) automatic speech recognition (ASR) systems. This
issue is more important in Transformer-base... | 2103.09903 | title_snapshot |
mahadeokar21_interspeech | Flexi-Transducer: Optimizing Latency, Accuracy and Compute for Multi-Domain On-Device Scenarios | [
"Jay Mahadeokar",
"Yangyang Shi",
"Yuan Shangguan",
"Chunyang Wu",
"Alex Xiao",
"Hang Su",
"Duc Le",
"Ozlem Kalinli",
"Christian Fuegen",
"Michael L. Seltzer"
] | https://www.isca-archive.org/interspeech_2021/mahadeokar21_interspeech.html | https://www.isca-archive.org/interspeech_2021/mahadeokar21_interspeech.pdf | 10.21437/Interspeech.2021-1921 | 2107-2111 | @inproceedings{mahadeokar21_interspeech,
title = {{Flexi-Transducer: Optimizing Latency, Accuracy and Compute for Multi-Domain On-Device Scenarios}},
author = {Jay Mahadeokar and Yangyang Shi and Yuan Shangguan and Chunyang Wu and Alex Xiao and Hang Su and Duc Le and Ozlem Kalinli and Christian Fuegen and Mi... | Often, the storage and computational constraints of embedded devices
demand that a single on-device ASR model serve multiple use-cases /
domains. In this paper, we propose a Flexible Transducer (FlexiT)
for on-device automatic speech recognition to flexibly deal with multiple
use-cases / domains with different accuracy... | 2104.02232 | title_judge |
falkowskigilski21_interspeech | Difference in Perceived Speech Signal Quality Assessment Among Monolingual and Bilingual Teenage Students | [
"Przemyslaw Falkowski-Gilski"
] | https://www.isca-archive.org/interspeech_2021/falkowskigilski21_interspeech.html | https://www.isca-archive.org/interspeech_2021/falkowskigilski21_interspeech.pdf | 10.21437/Interspeech.2021-16 | 2112-2116 | @inproceedings{falkowskigilski21_interspeech,
title = {{Difference in Perceived Speech Signal Quality Assessment Among Monolingual and Bilingual Teenage Students}},
author = {Przemyslaw Falkowski-Gilski},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2112--2116},
doi = {10.... | The user perceived quality is a mixture of factors, including the background
of an individual. The process of auditory perception is discussed in
a wide variety of fields, ranging from engineering to medicine. Many
studies examine the difference between musicians and non-musicians.
Since musical training develops music... | null | null |
schymura21_interspeech | PILOT: Introducing Transformers for Probabilistic Sound Event Localization | [
"Christopher Schymura",
"Benedikt Bönninghoff",
"Tsubasa Ochiai",
"Marc Delcroix",
"Keisuke Kinoshita",
"Tomohiro Nakatani",
"Shoko Araki",
"Dorothea Kolossa"
] | https://www.isca-archive.org/interspeech_2021/schymura21_interspeech.html | https://www.isca-archive.org/interspeech_2021/schymura21_interspeech.pdf | 10.21437/Interspeech.2021-124 | 2117-2121 | @inproceedings{schymura21_interspeech,
title = {{PILOT: Introducing Transformers for Probabilistic Sound Event Localization}},
author = {Christopher Schymura and Benedikt Bönninghoff and Tsubasa Ochiai and Marc Delcroix and Keisuke Kinoshita and Tomohiro Nakatani and Shoko Araki and Dorothea Kolossa},
year... | Sound event localization aims at estimating the positions of sound
sources in the environment with respect to an acoustic receiver (e.g.
a microphone array). Recent advances in this domain most prominently
focused on utilizing deep recurrent neural networks. Inspired by the
success of transformer architectures as a sui... | 2106.03903 | title_snapshot |
togami21_interspeech | Sound Source Localization with Majorization Minimization | [
"Masahito Togami",
"Robin Scheibler"
] | https://www.isca-archive.org/interspeech_2021/togami21_interspeech.html | https://www.isca-archive.org/interspeech_2021/togami21_interspeech.pdf | 10.21437/Interspeech.2021-126 | 2122-2126 | @inproceedings{togami21_interspeech,
title = {{Sound Source Localization with Majorization Minimization}},
author = {Masahito Togami and Robin Scheibler},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2122--2126},
doi = {10.21437/Interspeech.2021-126},
issn = {2958-1... | We propose a sound source localization technique that estimates a speech
source location without precise grid searching. The source location
is estimated in a parameter optimization manner to minimize the steered-response
power (SRP) function with the near-field assumption. Because there
is no closed-form solution for ... | null | null |
mittag21_interspeech | NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets | [
"Gabriel Mittag",
"Babak Naderi",
"Assmaa Chehadi",
"Sebastian Möller"
] | https://www.isca-archive.org/interspeech_2021/mittag21_interspeech.html | https://www.isca-archive.org/interspeech_2021/mittag21_interspeech.pdf | 10.21437/Interspeech.2021-299 | 2127-2131 | @inproceedings{mittag21_interspeech,
title = {{NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets}},
author = {Gabriel Mittag and Babak Naderi and Assmaa Chehadi and Sebastian Möller},
year = {2021},
booktitle = {{Interspeech 2021}},
pa... | In this paper, we present an update to the NISQA speech quality prediction
model that is focused on distortions that occur in communication networks.
In contrast to the previous version, the model is trained end-to-end
and the time-dependency modelling and time-pooling is achieved through
a Self-Attention mechanism. Be... | 2104.09494 | title_snapshot |
naderi21_interspeech | Subjective Evaluation of Noise Suppression Algorithms in Crowdsourcing | [
"Babak Naderi",
"Ross Cutler"
] | https://www.isca-archive.org/interspeech_2021/naderi21_interspeech.html | https://www.isca-archive.org/interspeech_2021/naderi21_interspeech.pdf | 10.21437/Interspeech.2021-343 | 2132-2136 | @inproceedings{naderi21_interspeech,
title = {{Subjective Evaluation of Noise Suppression Algorithms in Crowdsourcing}},
author = {Babak Naderi and Ross Cutler},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2132--2136},
doi = {10.21437/Interspeech.2021-343},
issn = ... | The quality of the speech communication systems, which include noise
suppression algorithms, are typically evaluated in laboratory experiments
according to the ITU-T Rec. P.835, in which participants rate background
noise, speech signal, and overall quality separately. This paper introduces
an open-source toolkit for c... | 2010.13200 | title_snapshot |
geng21_interspeech | Reliable Intensity Vector Selection for Multi-Source Direction-of-Arrival Estimation Using a Single Acoustic Vector Sensor | [
"Jianhua Geng",
"Sifan Wang",
"Juan Li",
"JingWei Li",
"Xin Lou"
] | https://www.isca-archive.org/interspeech_2021/geng21_interspeech.html | https://www.isca-archive.org/interspeech_2021/geng21_interspeech.pdf | 10.21437/Interspeech.2021-375 | 2137-2141 | @inproceedings{geng21_interspeech,
title = {{Reliable Intensity Vector Selection for Multi-Source Direction-of-Arrival Estimation Using a Single Acoustic Vector Sensor}},
author = {Jianhua Geng and Sifan Wang and Juan Li and JingWei Li and Xin Lou},
year = {2021},
booktitle = {{Interspeech 2021}},
... | In the context of multi-source direction of arrival (DOA) estimation
using a single acoustic vector sensor (AVS), the received signal is
usually a mixture of noise, reverberation and source signals. The identification
of the time-frequency (TF) bins that are dominated by the source signals
can significantly improve the... | null | null |
yu21_interspeech | MetricNet: Towards Improved Modeling For Non-Intrusive Speech Quality Assessment | [
"Meng Yu",
"Chunlei Zhang",
"Yong Xu",
"Shi-Xiong Zhang",
"Dong Yu"
] | https://www.isca-archive.org/interspeech_2021/yu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/yu21_interspeech.pdf | 10.21437/Interspeech.2021-659 | 2142-2146 | @inproceedings{yu21_interspeech,
title = {{MetricNet: Towards Improved Modeling For Non-Intrusive Speech Quality Assessment}},
author = {Meng Yu and Chunlei Zhang and Yong Xu and Shi-Xiong Zhang and Dong Yu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2142--2146},
doi = ... | The objective speech quality assessment is usually conducted by comparing
received speech signal with its clean reference, while human beings
are capable of evaluating the speech quality without any reference,
such as in the mean opinion score (MOS) tests. Non-intrusive speech
quality assessment has attracted much atte... | 2104.01227 | title_snapshot |
toma21_interspeech | CNN-Based Processing of Acoustic and Radio Frequency Signals for Speaker Localization from MAVs | [
"Andrea Toma",
"Daniele Salvati",
"Carlo Drioli",
"Gian Luca Foresti"
] | https://www.isca-archive.org/interspeech_2021/toma21_interspeech.html | https://www.isca-archive.org/interspeech_2021/toma21_interspeech.pdf | 10.21437/Interspeech.2021-886 | 2147-2151 | @inproceedings{toma21_interspeech,
title = {{CNN-Based Processing of Acoustic and Radio Frequency Signals for Speaker Localization from MAVs}},
author = {Andrea Toma and Daniele Salvati and Carlo Drioli and Gian Luca Foresti},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2147--215... | A novel speaker localization algorithm from micro aerial vehicles (MAVs)
is investigated. It introduces a joint direction of arrival (DOA) and
distance prediction method based on processing and fusion of the multi-channel
speech data with radio frequency (RF) measurements of the received
signal strength. Possible appli... | null | null |
itoyama21_interspeech | Assessment of von Mises-Bernoulli Deep Neural Network in Sound Source Localization | [
"Katsutoshi Itoyama",
"Yoshiya Morimoto",
"Shungo Masaki",
"Ryosuke Kojima",
"Kenji Nishida",
"Kazuhiro Nakadai"
] | https://www.isca-archive.org/interspeech_2021/itoyama21_interspeech.html | https://www.isca-archive.org/interspeech_2021/itoyama21_interspeech.pdf | 10.21437/Interspeech.2021-1050 | 2152-2156 | @inproceedings{itoyama21_interspeech,
title = {{Assessment of von Mises-Bernoulli Deep Neural Network in Sound Source Localization}},
author = {Katsutoshi Itoyama and Yoshiya Morimoto and Shungo Masaki and Ryosuke Kojima and Kenji Nishida and Kazuhiro Nakadai},
year = {2021},
booktitle = {{Interspee... | This paper addresses the properties and effectiveness of the von Mises-Bernoulli
deep neural network (vM-B DNN), a neural network capable of learning
periodic information, in sound source localization. The phase, which
is periodic information, is an important cue in sound source localization,
but typical neural network... | null | null |
liu21g_interspeech | Feature Fusion by Attention Networks for Robust DOA Estimation | [
"Rongliang Liu",
"Nengheng Zheng",
"Xi Chen"
] | https://www.isca-archive.org/interspeech_2021/liu21g_interspeech.html | https://www.isca-archive.org/interspeech_2021/liu21g_interspeech.pdf | 10.21437/Interspeech.2021-1051 | 2157-2161 | @inproceedings{liu21g_interspeech,
title = {{Feature Fusion by Attention Networks for Robust DOA Estimation}},
author = {Rongliang Liu and Nengheng Zheng and Xi Chen},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2157--2161},
doi = {10.21437/Interspeech.2021-1051},
issn ... | Direction of arrival (DOA) estimation is a key front-end technology
for many speech-based intelligent systems. Deep neural networks-based
DOA systems have recently demonstrated better performances than conventional
ones. However, most of the existing networks use only one specific
acoustical feature as input, limiting ... | null | null |
lin21f_interspeech | Far-Field Speaker Localization and Adaptive GLMB Tracking | [
"Shoufeng Lin",
"Zhaojie Luo"
] | https://www.isca-archive.org/interspeech_2021/lin21f_interspeech.html | https://www.isca-archive.org/interspeech_2021/lin21f_interspeech.pdf | 10.21437/Interspeech.2021-1160 | 2162-2166 | @inproceedings{lin21f_interspeech,
title = {{Far-Field Speaker Localization and Adaptive GLMB Tracking}},
author = {Shoufeng Lin and Zhaojie Luo},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2162--2166},
doi = {10.21437/Interspeech.2021-1160},
issn = {2958-1796},
} | In the speech signal processing area, far-field speaker localization
using only the audio modality has been a fundamental but challenging
problem, especially in presence of reverberation and a varying number
of moving speakers. Many existing methods use speech onsets as reliable
directional cues against reverberation a... | null | null |
narayanaswamy21_interspeech | On the Design of Deep Priors for Unsupervised Audio Restoration | [
"Vivek Sivaraman Narayanaswamy",
"Jayaraman J. Thiagarajan",
"Andreas Spanias"
] | https://www.isca-archive.org/interspeech_2021/narayanaswamy21_interspeech.html | https://www.isca-archive.org/interspeech_2021/narayanaswamy21_interspeech.pdf | 10.21437/Interspeech.2021-1890 | 2167-2171 | @inproceedings{narayanaswamy21_interspeech,
title = {{On the Design of Deep Priors for Unsupervised Audio Restoration}},
author = {Vivek Sivaraman Narayanaswamy and Jayaraman J. Thiagarajan and Andreas Spanias},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2167--2171},
doi ... | Unsupervised deep learning methods for solving audio restoration problems
extensively rely on carefully tailored neural architectures that carry
strong inductive biases for defining priors in the time or spectral
domain. In this context, lot of recent success has been achieved with
sophisticated convolutional network c... | 2104.07161 | title_snapshot |
chen21h_interspeech | Cramér-Rao Lower Bound for DOA Estimation with an Array of Directional Microphones in Reverberant Environments | [
"Weiguang Chen",
"Cheng Xue",
"Xionghu Zhong"
] | https://www.isca-archive.org/interspeech_2021/chen21h_interspeech.html | https://www.isca-archive.org/interspeech_2021/chen21h_interspeech.pdf | 10.21437/Interspeech.2021-2267 | 2172-2176 | @inproceedings{chen21h_interspeech,
title = {{Cramér-Rao Lower Bound for DOA Estimation with an Array of Directional Microphones in Reverberant Environments}},
author = {Weiguang Chen and Cheng Xue and Xionghu Zhong},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2172--2176},
doi... | Existing direction-of-arrival (DOA) estimation methods usually assume
that signals are received by an array of omnidirectional microphones.
The performance can be seriously degraded due to heavy reverberation
and noise. In this paper, DOA estimation using an array with directional
microphones is considered. As the sign... | null | null |
you21b_interspeech | GAN Vocoder: Multi-Resolution Discriminator Is All You Need | [
"Jaeseong You",
"Dalhyun Kim",
"Gyuhyeon Nam",
"Geumbyeol Hwang",
"Gyeongsu Chae"
] | https://www.isca-archive.org/interspeech_2021/you21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/you21b_interspeech.pdf | 10.21437/Interspeech.2021-41 | 2177-2181 | @inproceedings{you21b_interspeech,
title = {{GAN Vocoder: Multi-Resolution Discriminator Is All You Need}},
author = {Jaeseong You and Dalhyun Kim and Gyuhyeon Nam and Geumbyeol Hwang and Gyeongsu Chae},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2177--2181},
doi = {10.2... | Several of the latest GAN-based vocoders show remarkable achievements,
outperforming autoregressive and flow-based competitors in both qualitative
and quantitative measures while synthesizing orders of magnitude faster.
In this work, we hypothesize that the common factor underlying their
success is the multi-resolution... | 2103.05236 | title_snapshot |
cong21_interspeech | Glow-WaveGAN: Learning Speech Representations from GAN-Based Variational Auto-Encoder for High Fidelity Flow-Based Speech Synthesis | [
"Jian Cong",
"Shan Yang",
"Lei Xie",
"Dan Su"
] | https://www.isca-archive.org/interspeech_2021/cong21_interspeech.html | https://www.isca-archive.org/interspeech_2021/cong21_interspeech.pdf | 10.21437/Interspeech.2021-414 | 2182-2186 | @inproceedings{cong21_interspeech,
title = {{Glow-WaveGAN: Learning Speech Representations from GAN-Based Variational Auto-Encoder for High Fidelity Flow-Based Speech Synthesis}},
author = {Jian Cong and Shan Yang and Lei Xie and Dan Su},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | Current two-stage TTS framework typically integrates an acoustic model
with a vocoder — the acoustic model predicts a low resolution
intermediate representation such as Mel-spectrum while the vocoder
generates waveform from the intermediate representation. Although the
intermediate representation is served as a bridge,... | 2106.10831 | title_snapshot |
yoneyama21_interspeech | Unified Source-Filter GAN: Unified Source-Filter Network Based On Factorization of Quasi-Periodic Parallel WaveGAN | [
"Reo Yoneyama",
"Yi-Chiao Wu",
"Tomoki Toda"
] | https://www.isca-archive.org/interspeech_2021/yoneyama21_interspeech.html | https://www.isca-archive.org/interspeech_2021/yoneyama21_interspeech.pdf | 10.21437/Interspeech.2021-517 | 2187-2191 | @inproceedings{yoneyama21_interspeech,
title = {{Unified Source-Filter GAN: Unified Source-Filter Network Based On Factorization of Quasi-Periodic Parallel WaveGAN}},
author = {Reo Yoneyama and Yi-Chiao Wu and Tomoki Toda},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2187--2191},... | We propose a unified approach to data-driven source-filter modeling
using a single neural network for developing a neural vocoder capable
of generating high-quality synthetic speech waveforms while retaining
flexibility of the source-filter model to control their voice characteristics.
Our proposed network called unifi... | 2104.04668 | title_snapshot |
mizuta21_interspeech | Harmonic WaveGAN: GAN-Based Speech Waveform Generation Model with Harmonic Structure Discriminator | [
"Kazuki Mizuta",
"Tomoki Koriyama",
"Hiroshi Saruwatari"
] | https://www.isca-archive.org/interspeech_2021/mizuta21_interspeech.html | https://www.isca-archive.org/interspeech_2021/mizuta21_interspeech.pdf | 10.21437/Interspeech.2021-583 | 2192-2196 | @inproceedings{mizuta21_interspeech,
title = {{Harmonic WaveGAN: GAN-Based Speech Waveform Generation Model with Harmonic Structure Discriminator}},
author = {Kazuki Mizuta and Tomoki Koriyama and Hiroshi Saruwatari},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2192--2196},
doi... | This paper proposes Harmonic WaveGAN, a GAN-based waveform generation
model that focuses on the harmonic structure of a speech waveform.
Our proposed model uses two discriminators to capture characteristics
of a speech waveform in a time domain and in a frequency domain, respectively.
In one of them, a harmonic structu... | null | null |
kim21f_interspeech | Fre-GAN: Adversarial Frequency-Consistent Audio Synthesis | [
"Ji-Hoon Kim",
"Sang-Hoon Lee",
"Ji-Hyun Lee",
"Seong-Whan Lee"
] | https://www.isca-archive.org/interspeech_2021/kim21f_interspeech.html | https://www.isca-archive.org/interspeech_2021/kim21f_interspeech.pdf | 10.21437/Interspeech.2021-845 | 2197-2201 | @inproceedings{kim21f_interspeech,
title = {{Fre-GAN: Adversarial Frequency-Consistent Audio Synthesis}},
author = {Ji-Hoon Kim and Sang-Hoon Lee and Ji-Hyun Lee and Seong-Whan Lee},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2197--2201},
doi = {10.21437/Interspeech.2021... | Although recent works on neural vocoder have improved the quality of
synthesized audio, there still exists a gap between generated and ground-truth
audio in frequency space. This difference leads to spectral artifacts
such as hissing noise or reverberation, and thus degrades the sample
quality. In this paper, we propos... | 2106.02297 | title_snapshot |
yang21e_interspeech | GANSpeech: Adversarial Training for High-Fidelity Multi-Speaker Speech Synthesis | [
"Jinhyeok Yang",
"Jae-Sung Bae",
"Taejun Bak",
"Young-Ik Kim",
"Hoon-Young Cho"
] | https://www.isca-archive.org/interspeech_2021/yang21e_interspeech.html | https://www.isca-archive.org/interspeech_2021/yang21e_interspeech.pdf | 10.21437/Interspeech.2021-971 | 2202-2206 | @inproceedings{yang21e_interspeech,
title = {{GANSpeech: Adversarial Training for High-Fidelity Multi-Speaker Speech Synthesis}},
author = {Jinhyeok Yang and Jae-Sung Bae and Taejun Bak and Young-Ik Kim and Hoon-Young Cho},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2202--2206},... | Recent advances in neural multi-speaker text-to-speech (TTS) models
have enabled the generation of reasonably good speech quality with
a single model and made it possible to synthesize the speech of a speaker
with limited training data. Fine-tuning to the target speaker data
with the multi-speaker model can achieve bet... | 2106.15153 | title_snapshot |
jang21_interspeech | UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation | [
"Won Jang",
"Dan Lim",
"Jaesam Yoon",
"Bongwan Kim",
"Juntae Kim"
] | https://www.isca-archive.org/interspeech_2021/jang21_interspeech.html | https://www.isca-archive.org/interspeech_2021/jang21_interspeech.pdf | 10.21437/Interspeech.2021-1016 | 2207-2211 | @inproceedings{jang21_interspeech,
title = {{UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation}},
author = {Won Jang and Dan Lim and Jaesam Yoon and Bongwan Kim and Juntae Kim},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | Most neural vocoders employ band-limited mel-spectrograms to generate
waveforms. If full-band spectral features are used as the input, the
vocoder can be provided with as much acoustic information as possible.
However, in some models employing full-band mel-spectrograms, an over-smoothing
problem occurs as part of whic... | 2106.07889 | title_snapshot |
alradhi21_interspeech | Continuous Wavelet Vocoder-Based Decomposition of Parametric Speech Waveform Synthesis | [
"Mohammed Salah Al-Radhi",
"Tamás Gábor Csapó",
"Csaba Zainkó",
"Géza Németh"
] | https://www.isca-archive.org/interspeech_2021/alradhi21_interspeech.html | https://www.isca-archive.org/interspeech_2021/alradhi21_interspeech.pdf | 10.21437/Interspeech.2021-1600 | 2212-2216 | @inproceedings{alradhi21_interspeech,
title = {{Continuous Wavelet Vocoder-Based Decomposition of Parametric Speech Waveform Synthesis}},
author = {Mohammed Salah Al-Radhi and Tamás Gábor Csapó and Csaba Zainkó and Géza Németh},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2212--2... | To date, various speech technology systems have adopted the vocoder
approach, a method for synthesizing speech waveform that shows a major
role in the performance of statistical parametric speech synthesis.
However, conventional source-filter systems (i.e., STRAIGHT) and sinusoidal
models (i.e., MagPhase) tend to produ... | 2106.06863 | title_snapshot |
tobing21_interspeech | High-Fidelity and Low-Latency Universal Neural Vocoder Based on Multiband WaveRNN with Data-Driven Linear Prediction for Discrete Waveform Modeling | [
"Patrick Lumban Tobing",
"Tomoki Toda"
] | https://www.isca-archive.org/interspeech_2021/tobing21_interspeech.html | https://www.isca-archive.org/interspeech_2021/tobing21_interspeech.pdf | 10.21437/Interspeech.2021-1984 | 2217-2221 | @inproceedings{tobing21_interspeech,
title = {{High-Fidelity and Low-Latency Universal Neural Vocoder Based on Multiband WaveRNN with Data-Driven Linear Prediction for Discrete Waveform Modeling}},
author = {Patrick Lumban Tobing and Tomoki Toda},
year = {2021},
booktitle = {{Interspeech 2021}},
p... | This paper presents a novel high-fidelity and low-latency universal
neural vocoder framework based on multiband WaveRNN with data-driven
linear prediction for discrete waveform modeling (MWDLP). MWDLP employs
a coarse-fine bit WaveRNN architecture for 10-bit mu-law waveform modeling.
A sparse gated recurrent unit with ... | 2105.09856 | title_snapshot |
liu21h_interspeech | Basis-MelGAN: Efficient Neural Vocoder Based on Audio Decomposition | [
"Zhengxi Liu",
"Yanmin Qian"
] | https://www.isca-archive.org/interspeech_2021/liu21h_interspeech.html | https://www.isca-archive.org/interspeech_2021/liu21h_interspeech.pdf | 10.21437/Interspeech.2021-2173 | 2222-2226 | @inproceedings{liu21h_interspeech,
title = {{Basis-MelGAN: Efficient Neural Vocoder Based on Audio Decomposition}},
author = {Zhengxi Liu and Yanmin Qian},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2222--2226},
doi = {10.21437/Interspeech.2021-2173},
issn = {2958... | Recent studies have shown that neural vocoders based on generative
adversarial network (GAN) can generate audios with high quality. While
GAN based neural vocoders have shown to be computationally much more
efficient than those based on autoregressive predictions, the real-time
generation of the highest quality audio o... | 2106.13419 | title_snapshot |
hwang21_interspeech | High-Fidelity Parallel WaveGAN with Multi-Band Harmonic-Plus-Noise Model | [
"Min-Jae Hwang",
"Ryuichi Yamamoto",
"Eunwoo Song",
"Jae-Min Kim"
] | https://www.isca-archive.org/interspeech_2021/hwang21_interspeech.html | https://www.isca-archive.org/interspeech_2021/hwang21_interspeech.pdf | 10.21437/Interspeech.2021-976 | 2227-2231 | @inproceedings{hwang21_interspeech,
title = {{High-Fidelity Parallel WaveGAN with Multi-Band Harmonic-Plus-Noise Model}},
author = {Min-Jae Hwang and Ryuichi Yamamoto and Eunwoo Song and Jae-Min Kim},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2227--2231},
doi = {10.2143... | This paper proposes a multi-band harmonic-plus-noise (HN) Parallel
WaveGAN (PWG) vocoder. To generate a high-fidelity speech signal, it
is important to well-reflect the harmonic-noise characteristics of
the speech waveform in the time-frequency domain. However, it is difficult
for the conventional PWG model to accurate... | null | null |
chen21i_interspeech | SpecRec: An Alternative Solution for Improving End-to-End Speech-to-Text Translation via Spectrogram Reconstruction | [
"Junkun Chen",
"Mingbo Ma",
"Renjie Zheng",
"Liang Huang"
] | https://www.isca-archive.org/interspeech_2021/chen21i_interspeech.html | https://www.isca-archive.org/interspeech_2021/chen21i_interspeech.pdf | 10.21437/Interspeech.2021-733 | 2232-2236 | @inproceedings{chen21i_interspeech,
title = {{SpecRec: An Alternative Solution for Improving End-to-End Speech-to-Text Translation via Spectrogram Reconstruction}},
author = {Junkun Chen and Mingbo Ma and Renjie Zheng and Liang Huang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {... | End-to-end Speech-to-text Translation (E2E-ST), which directly translates
source language speech to target language text, is widely useful in
practice, but traditional cascaded approaches (ASR+MT) often suffer
from error propagation in the pipeline. On the other hand, existing
end-to-end solutions heavily depend on the... | 2010.11445 | title_judge |
cherry21_interspeech | Subtitle Translation as Markup Translation | [
"Colin Cherry",
"Naveen Arivazhagan",
"Dirk Padfield",
"Maxim Krikun"
] | https://www.isca-archive.org/interspeech_2021/cherry21_interspeech.html | https://www.isca-archive.org/interspeech_2021/cherry21_interspeech.pdf | 10.21437/Interspeech.2021-744 | 2237-2241 | @inproceedings{cherry21_interspeech,
title = {{Subtitle Translation as Markup Translation}},
author = {Colin Cherry and Naveen Arivazhagan and Dirk Padfield and Maxim Krikun},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2237--2241},
doi = {10.21437/Interspeech.2021-744},
... | Automatic subtitle translation is an important technology to make video
content available across language barriers. Subtitle translation complicates
the normal translation problem by adding the challenge of how to format
the system output into subtitles. We propose a simple technique that
treats subtitle translation as... | null | null |
wang21r_interspeech | Large-Scale Self- and Semi-Supervised Learning for Speech Translation | [
"Changhan Wang",
"Anne Wu",
"Juan Pino",
"Alexei Baevski",
"Michael Auli",
"Alexis Conneau"
] | https://www.isca-archive.org/interspeech_2021/wang21r_interspeech.html | https://www.isca-archive.org/interspeech_2021/wang21r_interspeech.pdf | 10.21437/Interspeech.2021-1912 | 2242-2246 | @inproceedings{wang21r_interspeech,
title = {{Large-Scale Self- and Semi-Supervised Learning for Speech Translation}},
author = {Changhan Wang and Anne Wu and Juan Pino and Alexei Baevski and Michael Auli and Alexis Conneau},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2242--2246... | In this paper, we improve speech translation (ST) through effectively
leveraging large quantities of unlabeled speech and text data in different
and complementary ways. We explore both pretraining and self-training
by using the large Libri-Light speech audio corpus and language modeling
with CommonCrawl. Our experiment... | 2104.06678 | title_snapshot |
wang21s_interspeech | CoVoST 2 and Massively Multilingual Speech Translation | [
"Changhan Wang",
"Anne Wu",
"Jiatao Gu",
"Juan Pino"
] | https://www.isca-archive.org/interspeech_2021/wang21s_interspeech.html | https://www.isca-archive.org/interspeech_2021/wang21s_interspeech.pdf | 10.21437/Interspeech.2021-2027 | 2247-2251 | @inproceedings{wang21s_interspeech,
title = {{CoVoST 2 and Massively Multilingual Speech Translation}},
author = {Changhan Wang and Anne Wu and Jiatao Gu and Juan Pino},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2247--2251},
doi = {10.21437/Interspeech.2021-2027},
iss... | Speech translation (ST) is an increasingly popular topic of research,
partly due to the development of benchmark datasets. Nevertheless,
current datasets cover a limited number of languages. With the aim
to foster research into massive multilingual ST and ST for low resource
languages, we release CoVoST 2, a large-scal... | 2007.10310 | title_judge |
cheng21_interspeech | AlloST: Low-Resource Speech Translation Without Source Transcription | [
"Yao-Fei Cheng",
"Hung-Shin Lee",
"Hsin-Min Wang"
] | https://www.isca-archive.org/interspeech_2021/cheng21_interspeech.html | https://www.isca-archive.org/interspeech_2021/cheng21_interspeech.pdf | 10.21437/Interspeech.2021-526 | 2252-2256 | @inproceedings{cheng21_interspeech,
title = {{AlloST: Low-Resource Speech Translation Without Source Transcription}},
author = {Yao-Fei Cheng and Hung-Shin Lee and Hsin-Min Wang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2252--2256},
doi = {10.21437/Interspeech.2021-52... | The end-to-end architecture has made promising progress in speech translation
(ST). However, the ST task is still challenging under low-resource
conditions. Most ST models have shown unsatisfactory results, especially
in the absence of word information from the source speech utterance.
In this study, we survey methods ... | 2105.00171 | title_snapshot |
effendi21_interspeech | Weakly-Supervised Speech-to-Text Mapping with Visually Connected Non-Parallel Speech-Text Data Using Cyclic Partially-Aligned Transformer | [
"Johanes Effendi",
"Sakriani Sakti",
"Satoshi Nakamura"
] | https://www.isca-archive.org/interspeech_2021/effendi21_interspeech.html | https://www.isca-archive.org/interspeech_2021/effendi21_interspeech.pdf | 10.21437/Interspeech.2021-970 | 2257-2261 | @inproceedings{effendi21_interspeech,
title = {{Weakly-Supervised Speech-to-Text Mapping with Visually Connected Non-Parallel Speech-Text Data Using Cyclic Partially-Aligned Transformer}},
author = {Johanes Effendi and Sakriani Sakti and Satoshi Nakamura},
year = {2021},
booktitle = {{Interspeech 20... | Despite the successful development of automatic speech recognition
(ASR) systems for several of the world’s major languages, they
require a tremendous amount of parallel speech-text data. Unfortunately,
for many other languages, such resources are usually unavailable. This
study addresses the speech-to-text mapping pro... | null | null |
tokuyama21_interspeech | Transcribing Paralinguistic Acoustic Cues to Target Language Text in Transformer-Based Speech-to-Text Translation | [
"Hirotaka Tokuyama",
"Sakriani Sakti",
"Katsuhito Sudoh",
"Satoshi Nakamura"
] | https://www.isca-archive.org/interspeech_2021/tokuyama21_interspeech.html | https://www.isca-archive.org/interspeech_2021/tokuyama21_interspeech.pdf | 10.21437/Interspeech.2021-1020 | 2262-2266 | @inproceedings{tokuyama21_interspeech,
title = {{Transcribing Paralinguistic Acoustic Cues to Target Language Text in Transformer-Based Speech-to-Text Translation}},
author = {Hirotaka Tokuyama and Sakriani Sakti and Katsuhito Sudoh and Satoshi Nakamura},
year = {2021},
booktitle = {{Interspeech 202... | In spoken communication, a speaker may convey their message in words
(linguistic cues) with supplemental information (paralinguistic cues)
such as emotion and emphasis. Transforming all spoken information into
a written or verbal form is not trivial, especially if the transformation
has to be done across languages. Mos... | null | null |
ye21_interspeech | End-to-End Speech Translation via Cross-Modal Progressive Training | [
"Rong Ye",
"Mingxuan Wang",
"Lei Li"
] | https://www.isca-archive.org/interspeech_2021/ye21_interspeech.html | https://www.isca-archive.org/interspeech_2021/ye21_interspeech.pdf | 10.21437/Interspeech.2021-1065 | 2267-2271 | @inproceedings{ye21_interspeech,
title = {{End-to-End Speech Translation via Cross-Modal Progressive Training}},
author = {Rong Ye and Mingxuan Wang and Lei Li},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2267--2271},
doi = {10.21437/Interspeech.2021-1065},
issn =... | End-to-end speech translation models have become a new trend in research
due to their potential of reducing error propagation. However, these
models still suffer from the challenge of data scarcity. How to effectively
use unlabeled or other parallel corpora from machine translation is
promising but still an open proble... | 2104.10380 | title_snapshot |
ko21_interspeech | ASR Posterior-Based Loss for Multi-Task End-to-End Speech Translation | [
"Yuka Ko",
"Katsuhito Sudoh",
"Sakriani Sakti",
"Satoshi Nakamura"
] | https://www.isca-archive.org/interspeech_2021/ko21_interspeech.html | https://www.isca-archive.org/interspeech_2021/ko21_interspeech.pdf | 10.21437/Interspeech.2021-1105 | 2272-2276 | @inproceedings{ko21_interspeech,
title = {{ASR Posterior-Based Loss for Multi-Task End-to-End Speech Translation}},
author = {Yuka Ko and Katsuhito Sudoh and Sakriani Sakti and Satoshi Nakamura},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2272--2276},
doi = {10.21437/Int... | End-to-end speech translation (ST) translates source language speech
directly into target language without an intermediate automatic speech
recognition (ASR) output, as in a cascading approach. End-to-end ST
has the advantage of avoiding error propagation from the intermediate
ASR results, but its performance still lag... | null | null |
perezgonzalezdemartos21_interspeech | Towards Simultaneous Machine Interpretation | [
"Alejandro Pérez-González-de-Martos",
"Javier Iranzo-Sánchez",
"Adrià Giménez Pastor",
"Javier Jorge",
"Joan-Albert Silvestre-Cerdà",
"Jorge Civera",
"Albert Sanchis",
"Alfons Juan"
] | https://www.isca-archive.org/interspeech_2021/perezgonzalezdemartos21_interspeech.html | https://www.isca-archive.org/interspeech_2021/perezgonzalezdemartos21_interspeech.pdf | 10.21437/Interspeech.2021-201 | 2277-2281 | @inproceedings{perezgonzalezdemartos21_interspeech,
title = {{Towards Simultaneous Machine Interpretation}},
author = {Alejandro Pérez-González-de-Martos and Javier Iranzo-Sánchez and Adrià Giménez Pastor and Javier Jorge and Joan-Albert Silvestre-Cerdà and Jorge Civera and Albert Sanchis and Alfons Juan},
... | Automatic speech-to-speech translation (S2S) is one of the most challenging
speech and language processing tasks, especially when considering its
application to real-time settings. Recent advances on streaming Automatic
Speech Recognition (ASR), simultaneous Machine Translation (MT) and
incremental neural Text-To-Speec... | null | null |
martucci21_interspeech | Lexical Modeling of ASR Errors for Robust Speech Translation | [
"Giuseppe Martucci",
"Mauro Cettolo",
"Matteo Negri",
"Marco Turchi"
] | https://www.isca-archive.org/interspeech_2021/martucci21_interspeech.html | https://www.isca-archive.org/interspeech_2021/martucci21_interspeech.pdf | 10.21437/Interspeech.2021-265 | 2282-2286 | @inproceedings{martucci21_interspeech,
title = {{Lexical Modeling of ASR Errors for Robust Speech Translation}},
author = {Giuseppe Martucci and Mauro Cettolo and Matteo Negri and Marco Turchi},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2282--2286},
doi = {10.21437/Inte... | Error propagation from automatic speech recognition (ASR) to machine
translation (MT) is a critical issue for the (still) dominant cascade approach to speech translation. To robustify MT to ill-formed inputs,
we propose a technique to artificially corrupt clean transcripts so
as to emulate noisy automatic transcripts. ... | null | null |
vyas21_interspeech | Optimally Encoding Inductive Biases into the Transformer Improves End-to-End Speech Translation | [
"Piyush Vyas",
"Anastasia Kuznetsova",
"Donald S. Williamson"
] | https://www.isca-archive.org/interspeech_2021/vyas21_interspeech.html | https://www.isca-archive.org/interspeech_2021/vyas21_interspeech.pdf | 10.21437/Interspeech.2021-2007 | 2287-2291 | @inproceedings{vyas21_interspeech,
title = {{Optimally Encoding Inductive Biases into the Transformer Improves End-to-End Speech Translation}},
author = {Piyush Vyas and Anastasia Kuznetsova and Donald S. Williamson},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2287--2291},
doi... | Transformer-based encoder-decoder architectures have recently shown
promising results in end-to-end speech translation. However, the content-based
attention mechanism employed by the Transformer was designed for text
sequences and can only encode global inductive bias, that alone is
not sufficient for learning good rep... | null | null |
ananthanarayana21_interspeech | Effects of Feature Scaling and Fusion on Sign Language Translation | [
"Tejaswini Ananthanarayana",
"Lipisha Chaudhary",
"Ifeoma Nwogu"
] | https://www.isca-archive.org/interspeech_2021/ananthanarayana21_interspeech.html | https://www.isca-archive.org/interspeech_2021/ananthanarayana21_interspeech.pdf | 10.21437/Interspeech.2021-1863 | 2292-2296 | @inproceedings{ananthanarayana21_interspeech,
title = {{Effects of Feature Scaling and Fusion on Sign Language Translation}},
author = {Tejaswini Ananthanarayana and Lipisha Chaudhary and Ifeoma Nwogu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2292--2296},
doi = {10.21... | Sign language translation without transcription has only recently started
to gain attention. In our work, we focus on improving the state-of-the-art
translation by introducing a multi-feature fusion architecture with
enhanced input features. As sign language is challenging to segment,
we obtain the input features by ex... | null | null |
alenin21_interspeech | The ID R&D System Description for Short-Duration Speaker Verification Challenge 2021 | [
"Alexander Alenin",
"Anton Okhotnikov",
"Rostislav Makarov",
"Nikita Torgashov",
"Ilya Shigabeev",
"Konstantin Simonchik"
] | https://www.isca-archive.org/interspeech_2021/alenin21_interspeech.html | https://www.isca-archive.org/interspeech_2021/alenin21_interspeech.pdf | 10.21437/Interspeech.2021-1553 | 2297-2301 | @inproceedings{alenin21_interspeech,
title = {{The ID R&D System Description for Short-Duration Speaker Verification Challenge 2021}},
author = {Alexander Alenin and Anton Okhotnikov and Rostislav Makarov and Nikita Torgashov and Ilya Shigabeev and Konstantin Simonchik},
year = {2021},
booktitle = {... | This paper describes ID R&D team submission to the text-independent
task of the Short-duration Speaker Verification (SdSV) Challenge 2021.
The top performed system is a fusion of 9 Convolutional Neural Networks
based on the ResNet architecture. Experiments’ results of optimal
NN architecture search are shown. We also p... | null | null |
thienpondt21_interspeech | Integrating Frequency Translational Invariance in TDNNs and Frequency Positional Information in 2D ResNets to Enhance Speaker Verification | [
"Jenthe Thienpondt",
"Brecht Desplanques",
"Kris Demuynck"
] | https://www.isca-archive.org/interspeech_2021/thienpondt21_interspeech.html | https://www.isca-archive.org/interspeech_2021/thienpondt21_interspeech.pdf | 10.21437/Interspeech.2021-1570 | 2302-2306 | @inproceedings{thienpondt21_interspeech,
title = {{Integrating Frequency Translational Invariance in TDNNs and Frequency Positional Information in 2D ResNets to Enhance Speaker Verification}},
author = {Jenthe Thienpondt and Brecht Desplanques and Kris Demuynck},
year = {2021},
booktitle = {{Intersp... | This paper describes the IDLab submission for the text-independent
task of the Short-duration Speaker Verification Challenge 2021 (SdSVC-21).
This speaker verification competition focuses on short duration test
recordings and cross-lingual trials, along with the constraint of limited
availability of in-domain DeepMine ... | 2104.02370 | title_snapshot |
gusev21_interspeech | SdSVC Challenge 2021: Tips and Tricks to Boost the Short-Duration Speaker Verification System Performance | [
"Aleksei Gusev",
"Alisa Vinogradova",
"Sergey Novoselov",
"Sergei Astapov"
] | https://www.isca-archive.org/interspeech_2021/gusev21_interspeech.html | https://www.isca-archive.org/interspeech_2021/gusev21_interspeech.pdf | 10.21437/Interspeech.2021-1737 | 2307-2311 | @inproceedings{gusev21_interspeech,
title = {{SdSVC Challenge 2021: Tips and Tricks to Boost the Short-Duration Speaker Verification System Performance}},
author = {Aleksei Gusev and Alisa Vinogradova and Sergey Novoselov and Sergei Astapov},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | This paper presents speaker recognition (SR) systems for the text-independent
speaker verification under the cross-lingual (English vs Persian) task
(task 2) of the Short-duration Speaker Verification Challenge (SdSVC)
2021. We present the description of applied ResNet-like and ECAPA-TDNN-like
topology design solutions... | null | null |
kang21_interspeech | Team02 Text-Independent Speaker Verification System for SdSV Challenge 2021 | [
"Woo Hyun Kang",
"Nam Soo Kim"
] | https://www.isca-archive.org/interspeech_2021/kang21_interspeech.html | https://www.isca-archive.org/interspeech_2021/kang21_interspeech.pdf | 10.21437/Interspeech.2021-249 | 2312-2316 | @inproceedings{kang21_interspeech,
title = {{Team02 Text-Independent Speaker Verification System for SdSV Challenge 2021}},
author = {Woo Hyun Kang and Nam Soo Kim},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2312--2316},
doi = {10.21437/Interspeech.2021-249},
issn ... | In this paper, we provide description of our submitted systems to the
Short Duration Speaker Verification (SdSV) Challenge 2021 Task 2. The
challenge provides a difficult set of cross-language text-independent
speaker verification trials. Our submissions employ ResNet-based embedding
networks which are trained using va... | null | null |
qin21_interspeech | Our Learned Lessons from Cross-Lingual Speaker Verification: The CRMI-DKU System Description for the Short-Duration Speaker Verification Challenge 2021 | [
"Xiaoyi Qin",
"Chao Wang",
"Yong Ma",
"Min Liu",
"Shilei Zhang",
"Ming Li"
] | https://www.isca-archive.org/interspeech_2021/qin21_interspeech.html | https://www.isca-archive.org/interspeech_2021/qin21_interspeech.pdf | 10.21437/Interspeech.2021-398 | 2317-2321 | @inproceedings{qin21_interspeech,
title = {{Our Learned Lessons from Cross-Lingual Speaker Verification: The CRMI-DKU System Description for the Short-Duration Speaker Verification Challenge 2021}},
author = {Xiaoyi Qin and Chao Wang and Yong Ma and Min Liu and Shilei Zhang and Ming Li},
year = {2021}... | In this paper, we present our CRMI-DKU system description for the Short-duration
Speaker Verification Challenge (SdSVC) 2021. We introduce the whole
pipeline of our cross-lingual speaker verification system, including
data preprocessing, training strategy, utterance-level speaker embedding
extractor, domain-adaptation,... | null | null |
zhang21o_interspeech | Investigation of IMU&Elevoc Submission for the Short-Duration Speaker Verification Challenge 2021 | [
"Peng Zhang",
"Peng Hu",
"Xueliang Zhang"
] | https://www.isca-archive.org/interspeech_2021/zhang21o_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhang21o_interspeech.pdf | 10.21437/Interspeech.2021-743 | 2322-2326 | @inproceedings{zhang21o_interspeech,
title = {{Investigation of IMU&Elevoc Submission for the Short-Duration Speaker Verification Challenge 2021}},
author = {Peng Zhang and Peng Hu and Xueliang Zhang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2322--2326},
doi = {10.214... | In this paper, we present the IMU&Elevoc systems submitted to the
Short-duration Verification Challenge (SdSVC) 2021. Our submissions
focus on both text-dependent speaker verification (Task 1) and text-independent
speaker verification (Task 2). First, we investigate several frame-level
feature extractor architectures b... | null | null |
yan21_interspeech | The Sogou System for Short-Duration Speaker Verification Challenge 2021 | [
"Jie Yan",
"Shengyu Yao",
"Yiqian Pan",
"Wei Chen"
] | https://www.isca-archive.org/interspeech_2021/yan21_interspeech.html | https://www.isca-archive.org/interspeech_2021/yan21_interspeech.pdf | 10.21437/Interspeech.2021-965 | 2327-2331 | @inproceedings{yan21_interspeech,
title = {{The Sogou System for Short-Duration Speaker Verification Challenge 2021}},
author = {Jie Yan and Shengyu Yao and Yiqian Pan and Wei Chen},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2327--2331},
doi = {10.21437/Interspeech.2021... | In this paper we present our system for the task 2 of the Short-duration
Speaker Verification (SdSV) Challenge 2021. This task focuses on benchmarking
and varying degrees of phonetic variability analysis of short-duration
speaker recognition system. The main difficulty exists in the variance
between cross-lingual trial... | null | null |
han21c_interspeech | The SJTU System for Short-Duration Speaker Verification Challenge 2021 | [
"Bing Han",
"Zhengyang Chen",
"Zhikai Zhou",
"Yanmin Qian"
] | https://www.isca-archive.org/interspeech_2021/han21c_interspeech.html | https://www.isca-archive.org/interspeech_2021/han21c_interspeech.pdf | 10.21437/Interspeech.2021-2136 | 2332-2336 | @inproceedings{han21c_interspeech,
title = {{The SJTU System for Short-Duration Speaker Verification Challenge 2021}},
author = {Bing Han and Zhengyang Chen and Zhikai Zhou and Yanmin Qian},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2332--2336},
doi = {10.21437/Interspe... | This paper presents the SJTU system for both text-dependent and text-independent
tasks in short-duration speaker verification (SdSV) challenge 2021.
In this challenge, we explored different strong embedding extractors
to extract robust speaker embedding. For text-independent task, language-dependent
adaptive snorm is e... | 2208.01933 | title_snapshot |
raj21b_interspeech | Reformulating DOVER-Lap Label Mapping as a Graph Partitioning Problem | [
"Desh Raj",
"Sanjeev Khudanpur"
] | https://www.isca-archive.org/interspeech_2021/raj21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/raj21b_interspeech.pdf | 10.21437/Interspeech.2021-323 | 2351-2355 | @inproceedings{raj21b_interspeech,
title = {{Reformulating DOVER-Lap Label Mapping as a Graph Partitioning Problem}},
author = {Desh Raj and Sanjeev Khudanpur},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2351--2355},
doi = {10.21437/Interspeech.2021-323},
issn = {... | We recently proposed DOVER-Lap, a method for combining overlap-aware
speaker diarization system outputs. DOVER-Lap improved upon its predecessor
DOVER by using a label mapping method based on globally-informed greedy
search. In this paper, we analyze this label mapping in the framework
of a maximum orthogonal graph par... | 2104.01954 | title_snapshot |
tak21_interspeech | Graph Attention Networks for Anti-Spoofing | [
"Hemlata Tak",
"Jee-weon Jung",
"Jose Patino",
"Massimiliano Todisco",
"Nicholas Evans"
] | https://www.isca-archive.org/interspeech_2021/tak21_interspeech.html | https://www.isca-archive.org/interspeech_2021/tak21_interspeech.pdf | 10.21437/Interspeech.2021-993 | 2356-2360 | @inproceedings{tak21_interspeech,
title = {{Graph Attention Networks for Anti-Spoofing}},
author = {Hemlata Tak and Jee-weon Jung and Jose Patino and Massimiliano Todisco and Nicholas Evans},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2356--2360},
doi = {10.21437/Intersp... | The cues needed to detect spoofing attacks against automatic speaker
verification are often located in specific spectral sub-bands or temporal
segments. Previous works show the potential to learn these using either
spectral or temporal self-attention mechanisms but not the relationships
between neighbouring sub-bands o... | 2104.03654 | title_snapshot |
mingote21_interspeech | Log-Likelihood-Ratio Cost Function as Objective Loss for Speaker Verification Systems | [
"Victoria Mingote",
"Antonio Miguel",
"Alfonso Ortega",
"Eduardo Lleida"
] | https://www.isca-archive.org/interspeech_2021/mingote21_interspeech.html | https://www.isca-archive.org/interspeech_2021/mingote21_interspeech.pdf | 10.21437/Interspeech.2021-1085 | 2361-2365 | @inproceedings{mingote21_interspeech,
title = {{Log-Likelihood-Ratio Cost Function as Objective Loss for Speaker Verification Systems}},
author = {Victoria Mingote and Antonio Miguel and Alfonso Ortega and Eduardo Lleida},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2361--2365},
... | Many recent studies in Speaker Verification (SV) have been focused
on the design of the most appropriate training loss function, which
plays an important role to improve the recognition ability of the systems.
However, the verification loss functions created often do not take
into account the performance measures which... | null | null |
peng21c_interspeech | Effective Phase Encoding for End-To-End Speaker Verification | [
"Junyi Peng",
"Xiaoyang Qu",
"Rongzhi Gu",
"Jianzong Wang",
"Jing Xiao",
"Lukáš Burget",
"Jan Černocký"
] | https://www.isca-archive.org/interspeech_2021/peng21c_interspeech.html | https://www.isca-archive.org/interspeech_2021/peng21c_interspeech.pdf | 10.21437/Interspeech.2021-2025 | 2366-2370 | @inproceedings{peng21c_interspeech,
title = {{Effective Phase Encoding for End-To-End Speaker Verification}},
author = {Junyi Peng and Xiaoyang Qu and Rongzhi Gu and Jianzong Wang and Jing Xiao and Lukáš Burget and Jan Černocký},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2366--... | The widely used magnitude spectrum based features have shown their
superiority in the field of speech processing. In contrast, the importance
of phase spectrum is always ignored. This is because the patterns hidden
in phase cannot be intuitively modelled and interpreted, due to phase
wrapping phenomenon. In this paper,... | null | null |
nguyen21d_interspeech | Impact of Encoding and Segmentation Strategies on End-to-End Simultaneous Speech Translation | [
"Ha Nguyen",
"Yannick Estève",
"Laurent Besacier"
] | https://www.isca-archive.org/interspeech_2021/nguyen21d_interspeech.html | https://www.isca-archive.org/interspeech_2021/nguyen21d_interspeech.pdf | 10.21437/Interspeech.2021-608 | 2371-2375 | @inproceedings{nguyen21d_interspeech,
title = {{Impact of Encoding and Segmentation Strategies on End-to-End Simultaneous Speech Translation}},
author = {Ha Nguyen and Yannick Estève and Laurent Besacier},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2371--2375},
doi = {10... | Boosted by the simultaneous translation shared task at IWSLT 2020,
promising end-to-end online speech translation approaches were recently
proposed. They consist in incrementally encoding a speech input (in
a source language) and decoding the corresponding text (in a target
language) with the best possible trade-off be... | 2104.14470 | title_snapshot |
machacek21_interspeech | Lost in Interpreting: Speech Translation from Source or Interpreter? | [
"Dominik Macháček",
"Matúš Žilinec",
"Ondřej Bojar"
] | https://www.isca-archive.org/interspeech_2021/machacek21_interspeech.html | https://www.isca-archive.org/interspeech_2021/machacek21_interspeech.pdf | 10.21437/Interspeech.2021-2232 | 2376-2380 | @inproceedings{machacek21_interspeech,
title = {{Lost in Interpreting: Speech Translation from Source or Interpreter?}},
author = {Dominik Macháček and Matúš Žilinec and Ondřej Bojar},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2376--2380},
doi = {10.21437/Interspeech.20... | Interpreters facilitate multi-lingual meetings but the affordable set
of languages is often smaller than what is needed. Automatic simultaneous
speech translation can extend the set of provided languages. We investigate
if such an automatic system should rather follow the original speaker,
or an interpreter to achieve ... | 2106.09343 | title_snapshot |
pouthier21_interspeech | Active Speaker Detection as a Multi-Objective Optimization with Uncertainty-Based Multimodal Fusion | [
"Baptiste Pouthier",
"Laurent Pilati",
"Leela K. Gudupudi",
"Charles Bouveyron",
"Frederic Precioso"
] | https://www.isca-archive.org/interspeech_2021/pouthier21_interspeech.html | https://www.isca-archive.org/interspeech_2021/pouthier21_interspeech.pdf | 10.21437/Interspeech.2021-80 | 2381-2385 | @inproceedings{pouthier21_interspeech,
title = {{Active Speaker Detection as a Multi-Objective Optimization with Uncertainty-Based Multimodal Fusion}},
author = {Baptiste Pouthier and Laurent Pilati and Leela K. Gudupudi and Charles Bouveyron and Frederic Precioso},
year = {2021},
booktitle = {{Inte... | It is now well established from a variety of studies that there is
a significant benefit from combining video and audio data in detecting
active speakers. However, either of the modalities can potentially
mislead audiovisual fusion by inducing unreliable or deceptive information.
This paper outlines active speaker dete... | 2106.03821 | title_snapshot |
wallbridge21_interspeech | It’s Not What You Said, it’s How You Said it: Discriminative Perception of Speech as a Multichannel Communication System | [
"Sarenne Wallbridge",
"Peter Bell",
"Catherine Lai"
] | https://www.isca-archive.org/interspeech_2021/wallbridge21_interspeech.html | https://www.isca-archive.org/interspeech_2021/wallbridge21_interspeech.pdf | 10.21437/Interspeech.2021-1658 | 2386-2390 | @inproceedings{wallbridge21_interspeech,
title = {{It’s Not What You Said, it’s How You Said it: Discriminative Perception of Speech as a Multichannel Communication System}},
author = {Sarenne Wallbridge and Peter Bell and Catherine Lai},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | People convey information extremely effectively through spoken interaction
using multiple channels of information transmission: the lexical channel
of what is said, and the non-lexical channel of how it
is said. We propose studying human perception of spoken communication
as a means to better understand how information... | 2105.00260 | title_snapshot |
michael21_interspeech | Extending the Fullband E-Model Towards Background Noise, Bursty Packet Loss, and Conversational Degradations | [
"Thilo Michael",
"Gabriel Mittag",
"Andreas Bütow",
"Sebastian Möller"
] | https://www.isca-archive.org/interspeech_2021/michael21_interspeech.html | https://www.isca-archive.org/interspeech_2021/michael21_interspeech.pdf | 10.21437/Interspeech.2021-314 | 2391-2395 | @inproceedings{michael21_interspeech,
title = {{Extending the Fullband E-Model Towards Background Noise, Bursty Packet Loss, and Conversational Degradations}},
author = {Thilo Michael and Gabriel Mittag and Andreas Bütow and Sebastian Möller},
year = {2021},
booktitle = {{Interspeech 2021}},
pages... | Quality engineering of speech communication services in the full speech
transmission band (0–20,000 Hz) is facilitated by the fullband
E-model, a planning tool that predicts overall quality on the basis
of parameters describing the setting of the service. We presented a
first version of this model at Interspeech 2019, ... | null | null |
bergler21_interspeech | ORCA-SLANG: An Automatic Multi-Stage Semi-Supervised Deep Learning Framework for Large-Scale Killer Whale Call Type Identification | [
"Christian Bergler",
"Manuel Schmitt",
"Andreas Maier",
"Helena Symonds",
"Paul Spong",
"Steven R. Ness",
"George Tzanetakis",
"Elmar Nöth"
] | https://www.isca-archive.org/interspeech_2021/bergler21_interspeech.html | https://www.isca-archive.org/interspeech_2021/bergler21_interspeech.pdf | 10.21437/Interspeech.2021-616 | 2396-2400 | @inproceedings{bergler21_interspeech,
title = {{ORCA-SLANG: An Automatic Multi-Stage Semi-Supervised Deep Learning Framework for Large-Scale Killer Whale Call Type Identification}},
author = {Christian Bergler and Manuel Schmitt and Andreas Maier and Helena Symonds and Paul Spong and Steven R. Ness and Georg... | Identification of animal-specific vocalization patterns is an imperative
requirement to decode animal communication. In bioacoustics, passive
acoustic recording setups are increasingly deployed to acquire large-scale
datasets. Previous knowledge about established animal-specific call
types is usually present due to his... | null | null |
boes21_interspeech | Audiovisual Transfer Learning for Audio Tagging and Sound Event Detection | [
"Wim Boes",
"Hugo Van hamme"
] | https://www.isca-archive.org/interspeech_2021/boes21_interspeech.html | https://www.isca-archive.org/interspeech_2021/boes21_interspeech.pdf | 10.21437/Interspeech.2021-695 | 2401-2405 | @inproceedings{boes21_interspeech,
title = {{Audiovisual Transfer Learning for Audio Tagging and Sound Event Detection}},
author = {Wim Boes and Hugo {Van hamme}},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2401--2405},
doi = {10.21437/Interspeech.2021-695},
issn ... | We study the merit of transfer learning for two sound recognition problems,
i.e., audio tagging and sound event detection. Employing feature fusion,
we adapt a baseline system utilizing only spectral acoustic inputs
to also make use of pretrained auditory and visual features, extracted
from networks built for different... | 2106.05408 | title_snapshot |
nessler21_interspeech | Non-Intrusive Speech Quality Assessment with Transfer Learning and Subject-Specific Scaling | [
"Natalia Nessler",
"Milos Cernak",
"Paolo Prandoni",
"Pablo Mainar"
] | https://www.isca-archive.org/interspeech_2021/nessler21_interspeech.html | https://www.isca-archive.org/interspeech_2021/nessler21_interspeech.pdf | 10.21437/Interspeech.2021-1685 | 2406-2410 | @inproceedings{nessler21_interspeech,
title = {{Non-Intrusive Speech Quality Assessment with Transfer Learning and Subject-Specific Scaling}},
author = {Natalia Nessler and Milos Cernak and Paolo Prandoni and Pablo Mainar},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2406--2410},... | In communication systems, it is crucial to estimate the perceived quality
of audio and speech. The industrial standards for many years have been
PESQ, 3QUEST, and POLQA, which are intrusive methods. This restricts
the possibilities of using these metrics in real-world conditions,
where we might not have access to the c... | null | null |
oncescu21_interspeech | Audio Retrieval with Natural Language Queries | [
"Andreea-Maria Oncescu",
"A. Sophia Koepke",
"João F. Henriques",
"Zeynep Akata",
"Samuel Albanie"
] | https://www.isca-archive.org/interspeech_2021/oncescu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/oncescu21_interspeech.pdf | 10.21437/Interspeech.2021-2227 | 2411-2415 | @inproceedings{oncescu21_interspeech,
title = {{Audio Retrieval with Natural Language Queries}},
author = {Andreea-Maria Oncescu and A. Sophia Koepke and João F. Henriques and Zeynep Akata and Samuel Albanie},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2411--2415},
doi =... | We consider the task of retrieving audio using free-form natural language
queries. To study this problem, which has received limited attention
in the existing literature, we introduce challenging new benchmarks
for text-based audio retrieval using text annotations sourced from
the AudioCaps and Clotho datasets. We th... | 2105.02192 | title_snapshot |
giollo21_interspeech | Bootstrap an End-to-End ASR System by Multilingual Training, Transfer Learning, Text-to-Text Mapping and Synthetic Audio | [
"Manuel Giollo",
"Deniz Gunceler",
"Yulan Liu",
"Daniel Willett"
] | https://www.isca-archive.org/interspeech_2021/giollo21_interspeech.html | https://www.isca-archive.org/interspeech_2021/giollo21_interspeech.pdf | 10.21437/Interspeech.2021-198 | 2416-2420 | @inproceedings{giollo21_interspeech,
title = {{Bootstrap an End-to-End ASR System by Multilingual Training, Transfer Learning, Text-to-Text Mapping and Synthetic Audio}},
author = {Manuel Giollo and Deniz Gunceler and Yulan Liu and Daniel Willett},
year = {2021},
booktitle = {{Interspeech 2021}},
... | Bootstrapping speech recognition on limited data resources has been
an area of active research for long. The recent transition to all-neural
models and end-to-end (E2E) training brought along particular challenges
as these models are known to be data hungry, but also came with opportunities
around language-agnostic rep... | 2011.12696 | title_snapshot |
pham21_interspeech | Efficient Weight Factorization for Multilingual Speech Recognition | [
"Ngoc-Quan Pham",
"Tuan-Nam Nguyen",
"Sebastian Stüker",
"Alex Waibel"
] | https://www.isca-archive.org/interspeech_2021/pham21_interspeech.html | https://www.isca-archive.org/interspeech_2021/pham21_interspeech.pdf | 10.21437/Interspeech.2021-216 | 2421-2425 | @inproceedings{pham21_interspeech,
title = {{Efficient Weight Factorization for Multilingual Speech Recognition}},
author = {Ngoc-Quan Pham and Tuan-Nam Nguyen and Sebastian Stüker and Alex Waibel},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2421--2425},
doi = {10.21437/... | End-to-end multilingual speech recognition involves using a single
model training on a compositional speech corpus including many languages,
resulting in a single neural network to handle transcribing different
languages. Due to the fact that each language in the training data
has different characteristics, the shared ... | 2105.03010 | title_snapshot |
conneau21_interspeech | Unsupervised Cross-Lingual Representation Learning for Speech Recognition | [
"Alexis Conneau",
"Alexei Baevski",
"Ronan Collobert",
"Abdelrahman Mohamed",
"Michael Auli"
] | https://www.isca-archive.org/interspeech_2021/conneau21_interspeech.html | https://www.isca-archive.org/interspeech_2021/conneau21_interspeech.pdf | 10.21437/Interspeech.2021-329 | 2426-2430 | @inproceedings{conneau21_interspeech,
title = {{Unsupervised Cross-Lingual Representation Learning for Speech Recognition}},
author = {Alexis Conneau and Alexei Baevski and Ronan Collobert and Abdelrahman Mohamed and Michael Auli},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2426... | This paper presents XLSR which learns cross-lingual speech representations
by pretraining a single model from the raw waveform of speech in multiple
languages. We build on wav2vec 2.0 which is trained by solving a contrastive
task over masked latent speech representations and jointly learns a
quantization of the latent... | 2006.13979 | title_snapshot |
hayakawa21_interspeech | Language and Speaker-Independent Feature Transformation for End-to-End Multilingual Speech Recognition | [
"Tomoaki Hayakawa",
"Chee Siang Leow",
"Akio Kobayashi",
"Takehito Utsuro",
"Hiromitsu Nishizaki"
] | https://www.isca-archive.org/interspeech_2021/hayakawa21_interspeech.html | https://www.isca-archive.org/interspeech_2021/hayakawa21_interspeech.pdf | 10.21437/Interspeech.2021-390 | 2431-2435 | @inproceedings{hayakawa21_interspeech,
title = {{Language and Speaker-Independent Feature Transformation for End-to-End Multilingual Speech Recognition}},
author = {Tomoaki Hayakawa and Chee Siang Leow and Akio Kobayashi and Takehito Utsuro and Hiromitsu Nishizaki},
year = {2021},
booktitle = {{Inte... | This paper proposes a method to improve the performance of multilingual
automatic speech recognition (ASR) systems through language- and speaker-independent
feature transformation in a framework of end-to-end (E2E) ASR. Specifically,
we propose a multi-task training method that combines a language recognizer
and a spea... | null | null |
n21_interspeech | Using Large Self-Supervised Models for Low-Resource Speech Recognition | [
"Krishna D. N",
"Pinyi Wang",
"Bruno Bozza"
] | https://www.isca-archive.org/interspeech_2021/n21_interspeech.html | https://www.isca-archive.org/interspeech_2021/n21_interspeech.pdf | 10.21437/Interspeech.2021-631 | 2436-2440 | @inproceedings{n21_interspeech,
title = {{Using Large Self-Supervised Models for Low-Resource Speech Recognition}},
author = {Krishna D. N and Pinyi Wang and Bruno Bozza},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2436--2440},
doi = {10.21437/Interspeech.2021-631},
is... | Recently, self-supervised pre-training has shown significant improvements
in many areas of machine learning, including speech and NLP. The self-supervised
models are trained on a large amount of unlabelled data to learn higher-level
representations for downstream tasks. In this work, we investigate
the effectiveness of... | null | null |
kumar21e_interspeech | Dual Script E2E Framework for Multilingual and Code-Switching ASR | [
"Mari Ganesh Kumar",
"Jom Kuriakose",
"Anand Thyagachandran",
"Arun Kumar A",
"Ashish Seth",
"Lodagala V.S.V. Durga Prasad",
"Saish Jaiswal",
"Anusha Prakash",
"Hema A. Murthy"
] | https://www.isca-archive.org/interspeech_2021/kumar21e_interspeech.html | https://www.isca-archive.org/interspeech_2021/kumar21e_interspeech.pdf | 10.21437/Interspeech.2021-978 | 2441-2445 | @inproceedings{kumar21e_interspeech,
title = {{Dual Script E2E Framework for Multilingual and Code-Switching ASR}},
author = {Mari Ganesh Kumar and Jom Kuriakose and Anand Thyagachandran and Arun Kumar A and Ashish Seth and Lodagala V.S.V. Durga Prasad and Saish Jaiswal and Anusha Prakash and Hema A. Murthy}... | India is home to multiple languages, and training automatic speech
recognition (ASR) systems is challenging. Over time, each language
has adopted words from other languages, such as English, leading to
code-mixing. Most Indian languages also have their own unique scripts,
which poses a major limitation in training mult... | 2106.01400 | title_snapshot |
diwan21_interspeech | MUCS 2021: Multilingual and Code-Switching ASR Challenges for Low Resource Indian Languages | [
"Anuj Diwan",
"Rakesh Vaideeswaran",
"Sanket Shah",
"Ankita Singh",
"Srinivasa Raghavan",
"Shreya Khare",
"Vinit Unni",
"Saurabh Vyas",
"Akash Rajpuria",
"Chiranjeevi Yarra",
"Ashish Mittal",
"Prasanta Kumar Ghosh",
"Preethi Jyothi",
"Kalika Bali",
"Vivek Seshadri",
"Sunayana Sitaram",... | https://www.isca-archive.org/interspeech_2021/diwan21_interspeech.html | https://www.isca-archive.org/interspeech_2021/diwan21_interspeech.pdf | 10.21437/Interspeech.2021-1339 | 2446-2450 | @inproceedings{diwan21_interspeech,
title = {{MUCS 2021: Multilingual and Code-Switching ASR Challenges for Low Resource Indian Languages}},
author = {Anuj Diwan and Rakesh Vaideeswaran and Sanket Shah and Ankita Singh and Srinivasa Raghavan and Shreya Khare and Vinit Unni and Saurabh Vyas and Akash Rajpuria... | Recently, there is an increasing interest in multilingual automatic
speech recognition (ASR) where a speech recognition system caters to
multiple low resource languages by taking advantage of low amounts
of labelled corpora in multiple languages. With multilingualism becoming
common in today’s world, there has been inc... | 2104.00235 | title_judge |
winata21_interspeech | Adapt-and-Adjust: Overcoming the Long-Tail Problem of Multilingual Speech Recognition | [
"Genta Indra Winata",
"Guangsen Wang",
"Caiming Xiong",
"Steven Hoi"
] | https://www.isca-archive.org/interspeech_2021/winata21_interspeech.html | https://www.isca-archive.org/interspeech_2021/winata21_interspeech.pdf | 10.21437/Interspeech.2021-1390 | 2451-2455 | @inproceedings{winata21_interspeech,
title = {{Adapt-and-Adjust: Overcoming the Long-Tail Problem of Multilingual Speech Recognition}},
author = {Genta Indra Winata and Guangsen Wang and Caiming Xiong and Steven Hoi},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2451--2455},
doi... | One crucial challenge of real-world multilingual speech recognition
is the long-tailed distribution problem, where some resource-rich languages
like English have abundant training data, but a long tail of low-resource
languages have varying amounts of limited training data. To overcome
the long-tail problem, in this pa... | 2012.01687 | title_snapshot |
sailor21_interspeech | SRI-B End-to-End System for Multilingual and Code-Switching ASR Challenges for Low Resource Indian Languages | [
"Hardik Sailor",
"Kiran Praveen T",
"Vikas Agrawal",
"Abhinav Jain",
"Abhishek Pandey"
] | https://www.isca-archive.org/interspeech_2021/sailor21_interspeech.html | https://www.isca-archive.org/interspeech_2021/sailor21_interspeech.pdf | 10.21437/Interspeech.2021-1578 | 2456-2460 | @inproceedings{sailor21_interspeech,
title = {{SRI-B End-to-End System for Multilingual and Code-Switching ASR Challenges for Low Resource Indian Languages}},
author = {Hardik Sailor and Kiran Praveen T and Vikas Agrawal and Abhinav Jain and Abhishek Pandey},
year = {2021},
booktitle = {{Interspeech... | This paper describes SRI-B’s end-to-end Automated Speech Recognition
(ASR) system proposed for the subtask-1 on multilingual ASR challenges
for Indian languages. Our end-to-end (E2E) ASR model is based on the
transformer architecture trained by jointly minimizing Connectionist
Temporal Classification (CTC) & Cross-Entr... | null | null |
li21f_interspeech | Hierarchical Phone Recognition with Compositional Phonetics | [
"Xinjian Li",
"Juncheng Li",
"Florian Metze",
"Alan W. Black"
] | https://www.isca-archive.org/interspeech_2021/li21f_interspeech.html | https://www.isca-archive.org/interspeech_2021/li21f_interspeech.pdf | 10.21437/Interspeech.2021-1803 | 2461-2465 | @inproceedings{li21f_interspeech,
title = {{Hierarchical Phone Recognition with Compositional Phonetics}},
author = {Xinjian Li and Juncheng Li and Florian Metze and Alan W. Black},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2461--2465},
doi = {10.21437/Interspeech.2021-... | There is growing interest in building phone recognition systems for
low-resource languages as the majority of languages do not have any
writing systems. Phone recognition systems proposed so far typically
derive their phone inventory from the training languages, therefore
the derived inventory could only cover a limite... | null | null |
chowdhury21_interspeech | Towards One Model to Rule All: Multilingual Strategy for Dialectal Code-Switching Arabic ASR | [
"Shammur Absar Chowdhury",
"Amir Hussein",
"Ahmed Abdelali",
"Ahmed Ali"
] | https://www.isca-archive.org/interspeech_2021/chowdhury21_interspeech.html | https://www.isca-archive.org/interspeech_2021/chowdhury21_interspeech.pdf | 10.21437/Interspeech.2021-1809 | 2466-2470 | @inproceedings{chowdhury21_interspeech,
title = {{Towards One Model to Rule All: Multilingual Strategy for Dialectal Code-Switching Arabic ASR}},
author = {Shammur Absar Chowdhury and Amir Hussein and Ahmed Abdelali and Ahmed Ali},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2466... | With the advent of globalization, there is an increasing demand for
multilingual automatic speech recognition (ASR), handling language
and dialectal variation of spoken content. Recent studies show its
efficacy over monolingual systems. In this study, we design a large
multilingual end-to-end ASR using self-attention b... | 2105.14779 | title_snapshot |
yan21b_interspeech | Differentiable Allophone Graphs for Language-Universal Speech Recognition | [
"Brian Yan",
"Siddharth Dalmia",
"David R. Mortensen",
"Florian Metze",
"Shinji Watanabe"
] | https://www.isca-archive.org/interspeech_2021/yan21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/yan21b_interspeech.pdf | 10.21437/Interspeech.2021-1944 | 2471-2475 | @inproceedings{yan21b_interspeech,
title = {{Differentiable Allophone Graphs for Language-Universal Speech Recognition}},
author = {Brian Yan and Siddharth Dalmia and David R. Mortensen and Florian Metze and Shinji Watanabe},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2471--2475... | Building language-universal speech recognition systems entails producing
phonological units of spoken sound that can be shared across languages.
While speech annotations at the language-specific phoneme or surface
levels are readily available, annotations at a universal phone level
are relatively rare and difficult to ... | 2107.11628 | title_snapshot |
martin21_interspeech | Automatic Speech Recognition Systems Errors for Objective Sleepiness Detection Through Voice | [
"Vincent P. Martin",
"Jean-Luc Rouas",
"Florian Boyer",
"Pierre Philip"
] | https://www.isca-archive.org/interspeech_2021/martin21_interspeech.html | https://www.isca-archive.org/interspeech_2021/martin21_interspeech.pdf | 10.21437/Interspeech.2021-291 | 2476-2480 | @inproceedings{martin21_interspeech,
title = {{Automatic Speech Recognition Systems Errors for Objective Sleepiness Detection Through Voice}},
author = {Vincent P. Martin and Jean-Luc Rouas and Florian Boyer and Pierre Philip},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2476--24... | Chronic sleepiness, and specifically Excessive Daytime Sleepiness (EDS),
impacts everyday life and increases the risks of accidents. Compared
with traditional measures (EEG), the detection of objective EDS through
voice benefits from its ease to be implemented in ecological conditions
and to be sober in terms of data p... | null | null |
gillick21_interspeech | Robust Laughter Detection in Noisy Environments | [
"Jon Gillick",
"Wesley Deng",
"Kimiko Ryokai",
"David Bamman"
] | https://www.isca-archive.org/interspeech_2021/gillick21_interspeech.html | https://www.isca-archive.org/interspeech_2021/gillick21_interspeech.pdf | 10.21437/Interspeech.2021-353 | 2481-2485 | @inproceedings{gillick21_interspeech,
title = {{Robust Laughter Detection in Noisy Environments}},
author = {Jon Gillick and Wesley Deng and Kimiko Ryokai and David Bamman},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2481--2485},
doi = {10.21437/Interspeech.2021-353},
... | We investigate the problem of automatically identifying and extracting
laughter from audio files in noisy environments. We conduct an empirical
evaluation of several machine learning models using audio data of varying
sound quality, finding that while previously published methods work
relatively well in controlled envi... | null | null |
nagano21_interspeech | Impact of Emotional State on Estimation of Willingness to Buy from Advertising Speech | [
"Mizuki Nagano",
"Yusuke Ijima",
"Sadao Hiroya"
] | https://www.isca-archive.org/interspeech_2021/nagano21_interspeech.html | https://www.isca-archive.org/interspeech_2021/nagano21_interspeech.pdf | 10.21437/Interspeech.2021-827 | 2486-2490 | @inproceedings{nagano21_interspeech,
title = {{Impact of Emotional State on Estimation of Willingness to Buy from Advertising Speech}},
author = {Mizuki Nagano and Yusuke Ijima and Sadao Hiroya},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2486--2490},
doi = {10.21437/Int... | The characteristics of a speaker’s voice can affect the perceived
impression or behavior of the listener. Previous studies of consumer
behavior have shown that this can be well explained by the emotion-mediated
behavior model. However, few studies of the emotion-mediated behavior
model have used advertising speech. In ... | null | null |
alsofyani21_interspeech | Stacked Recurrent Neural Networks for Speech-Based Inference of Attachment Condition in School Age Children | [
"Huda Alsofyani",
"Alessandro Vinciarelli"
] | https://www.isca-archive.org/interspeech_2021/alsofyani21_interspeech.html | https://www.isca-archive.org/interspeech_2021/alsofyani21_interspeech.pdf | 10.21437/Interspeech.2021-904 | 2491-2495 | @inproceedings{alsofyani21_interspeech,
title = {{Stacked Recurrent Neural Networks for Speech-Based Inference of Attachment Condition in School Age Children}},
author = {Huda Alsofyani and Alessandro Vinciarelli},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2491--2495},
doi ... | In Attachment Theory, children that have a positive perception of their
parents are said to be secure, while the others are said to be insecure.
Once adult, unless identified and supported early enough, insecure
children have higher chances to experience major issues (e.g., suicidal
tendencies and antisocial behavior).... | null | null |
aloshban21_interspeech | Language or Paralanguage, This is the Problem: Comparing Depressed and Non-Depressed Speakers Through the Analysis of Gated Multimodal Units | [
"Nujud Aloshban",
"Anna Esposito",
"Alessandro Vinciarelli"
] | https://www.isca-archive.org/interspeech_2021/aloshban21_interspeech.html | https://www.isca-archive.org/interspeech_2021/aloshban21_interspeech.pdf | 10.21437/Interspeech.2021-928 | 2496-2500 | @inproceedings{aloshban21_interspeech,
title = {{Language or Paralanguage, This is the Problem: Comparing Depressed and Non-Depressed Speakers Through the Analysis of Gated Multimodal Units}},
author = {Nujud Aloshban and Anna Esposito and Alessandro Vinciarelli},
year = {2021},
booktitle = {{Inters... | Speech-based depression detection has attracted significant attention
over the last years. A debated problem is whether it is better to use
language (what people say), paralanguage (how they say it) or a combination
of the two. This article addresses the question through the analysis
of a Gated Multimodal Unit trained ... | null | null |
tammewar21_interspeech | Emotion Carrier Recognition from Personal Narratives | [
"Aniruddha Tammewar",
"Alessandra Cervone",
"Giuseppe Riccardi"
] | https://www.isca-archive.org/interspeech_2021/tammewar21_interspeech.html | https://www.isca-archive.org/interspeech_2021/tammewar21_interspeech.pdf | 10.21437/Interspeech.2021-1100 | 2501-2505 | @inproceedings{tammewar21_interspeech,
title = {{Emotion Carrier Recognition from Personal Narratives}},
author = {Aniruddha Tammewar and Alessandra Cervone and Giuseppe Riccardi},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2501--2505},
doi = {10.21437/Interspeech.2021-1... | Personal Narratives (PN) — recollections of facts, events, and
thoughts from one’s own experience — are often used in
everyday conversations. So far, PNs have mainly been explored for tasks
such as valence prediction or emotion classification (e.g. happy,
sad ). However, these tasks might overlook more fine-grained inf... | 2008.07481 | title_snapshot |
condron21_interspeech | Non-Verbal Vocalisation and Laughter Detection Using Sequence-to-Sequence Models and Multi-Label Training | [
"Scott Condron",
"Georgia Clarke",
"Anita Klementiev",
"Daniela Morse-Kopp",
"Jack Parry",
"Dimitri Palaz"
] | https://www.isca-archive.org/interspeech_2021/condron21_interspeech.html | https://www.isca-archive.org/interspeech_2021/condron21_interspeech.pdf | 10.21437/Interspeech.2021-1159 | 2506-2510 | @inproceedings{condron21_interspeech,
title = {{Non-Verbal Vocalisation and Laughter Detection Using Sequence-to-Sequence Models and Multi-Label Training}},
author = {Scott Condron and Georgia Clarke and Anita Klementiev and Daniela Morse-Kopp and Jack Parry and Dimitri Palaz},
year = {2021},
bookti... | Non-verbal vocalisations (NVVs) such as laughter are an important part
of communication in social interactions and carry important information
about a speaker’s state or intention. There remains no clear
definition of NVVs and there is no clearly defined protocol for transcribing
or detecting NVVs. As such, the standar... | null | null |
cai21_interspeech | TDCA-Net: Time-Domain Channel Attention Network for Depression Detection | [
"Cong Cai",
"Mingyue Niu",
"Bin Liu",
"Jianhua Tao",
"Xuefei Liu"
] | https://www.isca-archive.org/interspeech_2021/cai21_interspeech.html | https://www.isca-archive.org/interspeech_2021/cai21_interspeech.pdf | 10.21437/Interspeech.2021-1176 | 2511-2515 | @inproceedings{cai21_interspeech,
title = {{TDCA-Net: Time-Domain Channel Attention Network for Depression Detection}},
author = {Cong Cai and Mingyue Niu and Bin Liu and Jianhua Tao and Xuefei Liu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2511--2515},
doi = {10.21437... | Depression is a psychiatric disorder and has many adverse effects on
our society. Some studies have shown that speech signals are closely
related to emotion and stress, and many speech-based automatic depression
detection methods have been proposed. However, previous work is based
on spectrogram or hand-crafted feature... | null | null |
botelho21_interspeech | Visual Speech for Obstructive Sleep Apnea Detection | [
"Catarina Botelho",
"Alberto Abad",
"Tanja Schultz",
"Isabel Trancoso"
] | https://www.isca-archive.org/interspeech_2021/botelho21_interspeech.html | https://www.isca-archive.org/interspeech_2021/botelho21_interspeech.pdf | 10.21437/Interspeech.2021-1717 | 2516-2520 | @inproceedings{botelho21_interspeech,
title = {{Visual Speech for Obstructive Sleep Apnea Detection}},
author = {Catarina Botelho and Alberto Abad and Tanja Schultz and Isabel Trancoso},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2516--2520},
doi = {10.21437/Interspeech.... | Obstructive sleep apnea (OSA) affects almost one billion people worldwide
and limits peoples’ quality of life substantially. Furthermore,
it is responsible for significant morbidity and mortality associated
with hypertension, cardiovascular diseases, work and traffic accidents.
Thus, the early detection of OSA can save... | null | null |
maruri21_interspeech | Analysis of Contextual Voice Changes in Remote Meetings | [
"Hector A. Cordourier Maruri",
"Sinem Aslan",
"Georg Stemmer",
"Nese Alyuz",
"Lama Nachman"
] | https://www.isca-archive.org/interspeech_2021/maruri21_interspeech.html | https://www.isca-archive.org/interspeech_2021/maruri21_interspeech.pdf | 10.21437/Interspeech.2021-1932 | 2521-2525 | @inproceedings{maruri21_interspeech,
title = {{Analysis of Contextual Voice Changes in Remote Meetings}},
author = {Hector A. Cordourier Maruri and Sinem Aslan and Georg Stemmer and Nese Alyuz and Lama Nachman},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2521--2525},
doi ... | People participating in remote meetings in open spaces might choose
to speak with a restrained voice due to concerns around privacy or
disturbing others. These contextual voice changes might impact the
quality of communications. To investigate how people adjust their voices
in certain situations, we performed an explor... | null | null |
seneviratne21_interspeech | Speech Based Depression Severity Level Classification Using a Multi-Stage Dilated CNN-LSTM Model | [
"Nadee Seneviratne",
"Carol Espy-Wilson"
] | https://www.isca-archive.org/interspeech_2021/seneviratne21_interspeech.html | https://www.isca-archive.org/interspeech_2021/seneviratne21_interspeech.pdf | 10.21437/Interspeech.2021-1967 | 2526-2530 | @inproceedings{seneviratne21_interspeech,
title = {{Speech Based Depression Severity Level Classification Using a Multi-Stage Dilated CNN-LSTM Model}},
author = {Nadee Seneviratne and Carol Espy-Wilson},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {2526--2530},
doi = {10.2... | Speech based depression classification has gained immense popularity
over the recent years. However, most of the classification studies
have focused on binary classification to distinguish depressed subjects
from non-depressed subjects. In this paper, we formulate the depression
classification task as a severity level ... | 2104.04195 | title_snapshot |
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