prompts stringlengths 81 413 | metrics_response stringlengths 0 371 |
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What metrics were used to measure the mllp_2021_streaming_filt model in the Europarl-ASR: A Large Corpus of Parliamentary Debates for Streaming ASR Benchmarking and Speech Data Filtering/Verbatimization paper on the Europarl-ASR EN MEP-test dataset? | WER |
What metrics were used to measure the mllp_2021_offline_verb model in the Europarl-ASR: A Large Corpus of Parliamentary Debates for Streaming ASR Benchmarking and Speech Data Filtering/Verbatimization paper on the Europarl-ASR EN Guest-test dataset? | WER |
What metrics were used to measure the mllp_2021_streaming_verb model in the Europarl-ASR: A Large Corpus of Parliamentary Debates for Streaming ASR Benchmarking and Speech Data Filtering/Verbatimization paper on the Europarl-ASR EN Guest-test dataset? | WER |
What metrics were used to measure the wav2vec_wav2letter model in the Self-training and Pre-training are Complementary for Speech Recognition paper on the LibriSpeech train-clean-100 test-clean dataset? | Word Error Rate (WER) |
What metrics were used to measure the SpeechStew (100M) model in the SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network paper on the AMI SDM1 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Vietnamese end-to-end speech recognition using wav2vec 2.0 by VietAI model in the Vietnamese end-to-end speech recognition using wav2vec 2.0 paper on the VIVOS dataset? | Test WER |
What metrics were used to measure the wav2vec2-base-vietnamese-160h (No Language Model) model in the Wav2vec2 Base Vietnamese 160h paper on the VIVOS dataset? | Test WER |
What metrics were used to measure the End-to-end LF-MMI model in the End-to-end speech recognition using lattice-free MMI paper on the Switchboard (300hr) dataset? | Word Error Rate (WER) |
What metrics were used to measure the Paraformer-large model in the FunASR: A Fundamental End-to-End Speech Recognition Toolkit paper on the AISHELL-2 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Paraformer model in the FunASR: A Fundamental End-to-End Speech Recognition Toolkit paper on the AISHELL-2 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Quartznet model in the MediaSpeech: Multilanguage ASR Benchmark and Dataset paper on the MediaSpeech dataset? | WER for Arabic, WER for French, WER for Spanish, WER for Turkish |
What metrics were used to measure the Wit model in the MediaSpeech: Multilanguage ASR Benchmark and Dataset paper on the MediaSpeech dataset? | WER for Arabic, WER for French, WER for Spanish, WER for Turkish |
What metrics were used to measure the Azure model in the MediaSpeech: Multilanguage ASR Benchmark and Dataset paper on the MediaSpeech dataset? | WER for Arabic, WER for French, WER for Spanish, WER for Turkish |
What metrics were used to measure the VOSK model in the MediaSpeech: Multilanguage ASR Benchmark and Dataset paper on the MediaSpeech dataset? | WER for Arabic, WER for French, WER for Spanish, WER for Turkish |
What metrics were used to measure the Google model in the MediaSpeech: Multilanguage ASR Benchmark and Dataset paper on the MediaSpeech dataset? | WER for Arabic, WER for French, WER for Spanish, WER for Turkish |
What metrics were used to measure the wav2vec model in the MediaSpeech: Multilanguage ASR Benchmark and Dataset paper on the MediaSpeech dataset? | WER for Arabic, WER for French, WER for Spanish, WER for Turkish |
What metrics were used to measure the Deepspeech model in the MediaSpeech: Multilanguage ASR Benchmark and Dataset paper on the MediaSpeech dataset? | WER for Arabic, WER for French, WER for Spanish, WER for Turkish |
What metrics were used to measure the Silero model in the MediaSpeech: Multilanguage ASR Benchmark and Dataset paper on the MediaSpeech dataset? | WER for Arabic, WER for French, WER for Spanish, WER for Turkish |
What metrics were used to measure the IBM (LSTM+Conformer encoder-decoder) model in the On the limit of English conversational speech recognition paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the IBM (LSTM encoder-decoder) model in the Single headed attention based sequence-to-sequence model for state-of-the-art results on Switchboard paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the ResNet + BiLSTMs acoustic model model in the English Conversational Telephone Speech Recognition by Humans and Machines paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the VGG/Resnet/LACE/BiLSTM acoustic model trained on SWB+Fisher+CH, N-gram + RNNLM language model trained on Switchboard+Fisher+Gigaword+Broadcast model in the The Microsoft 2016 Conversational Speech Recognition System paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the RNN + VGG + LSTM acoustic model trained on SWB+Fisher+CH, N-gram + "model M" + NNLM language model model in the The IBM 2016 English Conversational Telephone Speech Recognition System paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the HMM-BLSTM trained with MMI + data augmentation (speed) + iVectors + 3 regularizations + Fisher model in the paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the HMM-TDNN trained with MMI + data augmentation (speed) + iVectors + 3 regularizations + Fisher (10% / 15.1% respectively trained on SWBD only) model in the paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the CNN + Bi-RNN + CTC (speech to letters), 25.9% WER if trainedonlyon SWB model in the Deep Speech: Scaling up end-to-end speech recognition paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the HMM-TDNN + iVectors model in the paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the HMM-DNN +sMBR model in the paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the DNN + Dropout model in the Building DNN Acoustic Models for Large Vocabulary Speech Recognition paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the HMM-TDNN + pNorm + speed up/down speech model in the paper on the swb_hub_500 WER fullSWBCH dataset? | Percentage error |
What metrics were used to measure the MMSpeech With LM model in the MMSpeech: Multi-modal Multi-task Encoder-Decoder Pre-training for Speech Recognition paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the Paraformer-large model in the FunASR: A Fundamental End-to-End Speech Recognition Toolkit paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the SE-WSBO With LM model in the Improving Mandarin Speech Recogntion with Block-augmented Transformer paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the UMA model in the Unimodal Aggregation for CTC-based Speech Recognition paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the U2 model in the Unified Streaming and Non-streaming Two-pass End-to-end Model for Speech Recognition paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the CTC/Att model in the Unified Streaming and Non-streaming Two-pass End-to-end Model for Speech Recognition paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the Paraformer model in the FunASR: A Fundamental End-to-End Speech Recognition Toolkit paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the BAT model in the BAT: Boundary aware transducer for memory-efficient and low-latency ASR paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the CTC-CRF 4gram-LM model in the CAT: A CTC-CRF based ASR Toolkit Bridging the Hybrid and the End-to-end Approaches towards Data Efficiency and Low Latency paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the BRA-E model in the Beyond Universal Transformer: block reusing with adaptor in Transformer for automatic speech recognition paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the CTC/Att model in the A Comparative Study on Transformer vs RNN in Speech Applications paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the Att model in the End-to-end Speech Recognition with Adaptive Computation Steps paper on the AISHELL-1 dataset? | Word Error Rate (WER), Params(M) |
What metrics were used to measure the SpeechStew (100M) model in the SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network paper on the AMI IMH dataset? | Word Error Rate (WER) |
What metrics were used to measure the SpeechStew (100M) model in the SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network paper on the Switchboard SWBD dataset? | Word Error Rate (WER) |
What metrics were used to measure the wav2vec 2.0 Large-10h-LV-60k model in the wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations paper on the Libri-Light test-other dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the TDS 60k pseudo-label + CTC fine-tuning + 4gram-LM model in the Libri-Light: A Benchmark for ASR with Limited or No Supervision paper on the Libri-Light test-other dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the CPC unlab-60k+train-10h CPC pretrain + CTC fine-tuning + 4gram-LM model in the Libri-Light: A Benchmark for ASR with Limited or No Supervision paper on the Libri-Light test-other dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the CPC unlab-60k model in the Libri-Light: A Benchmark for ASR with Limited or No Supervision paper on the Libri-Light test-other dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the S6000h-n42-τ2 → 0.1 model in the Improving Unsupervised Sparsespeech Acoustic Models with Categorical Reparameterization paper on the Libri-Light test-other dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the wav2vec_wav2letter model in the Self-training and Pre-training are Complementary for Speech Recognition paper on the LibriSpeech train-clean-100 test-other dataset? | Word Error Rate (WER) |
What metrics were used to measure the SpeechStew (1B) model in the SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network paper on the CHiME-6 eval dataset? | Word Error Rate (WER) |
What metrics were used to measure the Triphone (39 features) + LDA and MLLT + SGMM model in the First Automatic Fongbe Continuous Speech Recognition System: Development of Acoustic Models and Language Models paper on the Fongbe audio dataset? | Word Error Rate (WER) |
What metrics were used to measure the Triphone (39 features) + LDA and MLLT + SAT and FMLLR model in the First Automatic Fongbe Continuous Speech Recognition System: Development of Acoustic Models and Language Models paper on the Fongbe audio dataset? | Word Error Rate (WER) |
What metrics were used to measure the Triphone (13 MFCC + delta + delta2) model in the First Automatic Fongbe Continuous Speech Recognition System: Development of Acoustic Models and Language Models paper on the Fongbe audio dataset? | Word Error Rate (WER) |
What metrics were used to measure the CTC-CRF ST-NAS model in the Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through Gradients paper on the WSJ dev93 dataset? | Word Error Rate (WER) |
What metrics were used to measure the CTC-CRF VGG-BLSTM model in the CAT: A CTC-CRF based ASR Toolkit Bridging the Hybrid and the End-to-end Approaches towards Data Efficiency and Low Latency paper on the WSJ dev93 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Convolutional Speech Recognition model in the CRF-based Single-stage Acoustic Modeling with CTC Topology paper on the WSJ dev93 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Convolutional Speech Recognition model in the Fully Convolutional Speech Recognition paper on the WSJ dev93 dataset? | Word Error Rate (WER) |
What metrics were used to measure the RAVEn Large model in the Jointly Learning Visual and Auditory Speech Representations from Raw Data paper on the LRS2 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Speechstew 100M model in the SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the tdnn + chain model in the Purely sequence-trained neural networks for ASR based on lattice-free MMI paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the CTC-CRF ST-NAS model in the Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through Gradients paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the End-to-end LF-MMI model in the End-to-end speech recognition using lattice-free MMI paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Transformer with Relaxed Attention model in the Relaxed Attention: A Simple Method to Boost Performance of End-to-End Automatic Speech Recognition paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the CTC-CRF VGG-BLSTM model in the CAT: A CTC-CRF based ASR Toolkit Bridging the Hybrid and the End-to-end Approaches towards Data Efficiency and Low Latency paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Espresso model in the Espresso: A Fast End-to-end Neural Speech Recognition Toolkit paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the TC-DNN-BLSTM-DNN model in the Deep Recurrent Neural Networks for Acoustic Modelling paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Convolutional Speech Recognition model in the Fully Convolutional Speech Recognition paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm* model in the paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Deep Speech 2 model in the Deep Speech 2: End-to-End Speech Recognition in English and Mandarin paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the CTC-CRF 4gram-LM model in the CRF-based Single-stage Acoustic Modeling with CTC Topology paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the CNN over RAW speech (wav) model in the paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the Jasper 10x3 model in the Jasper: An End-to-End Convolutional Neural Acoustic Model paper on the WSJ eval92 dataset? | Word Error Rate (WER) |
What metrics were used to measure the wav2vec 2.0 Large-10h-LV-60k model in the wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations paper on the Libri-Light test-clean dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the TDS 60k pseudo-label + CTC fine-tuning + 4gram-LM model in the Libri-Light: A Benchmark for ASR with Limited or No Supervision paper on the Libri-Light test-clean dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the CPC unlab-60k+train-10h CPC pretrain + CTC fine-tuning + 4gram-LM model in the Libri-Light: A Benchmark for ASR with Limited or No Supervision paper on the Libri-Light test-clean dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the CPC unlab-60k model in the Libri-Light: A Benchmark for ASR with Limited or No Supervision paper on the Libri-Light test-clean dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the S6000h-n42-τ2 → 0.1 model in the Improving Unsupervised Sparsespeech Acoustic Models with Categorical Reparameterization paper on the Libri-Light test-clean dataset? | Word Error Rate (WER), ABX-across, ABX-within |
What metrics were used to measure the wav2vec 2.0 model in the wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the vq-wav2vec model in the vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the LiGRU + Dropout + BatchNorm + Monophone Reg model in the The PyTorch-Kaldi Speech Recognition Toolkit paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the LSTM + Dropout + BatchNorm + Monophone Reg model in the The PyTorch-Kaldi Speech Recognition Toolkit paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the wav2vec model in the wav2vec: Unsupervised Pre-training for Speech Recognition paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the GRU + Dropout + BatchNorm + Monophone Reg model in the The PyTorch-Kaldi Speech Recognition Toolkit paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the Li-GRU + fMLLR features model in the Light Gated Recurrent Units for Speech Recognition paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the RNN + Dropout + BatchNorm + Monophone Reg model in the The PyTorch-Kaldi Speech Recognition Toolkit paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the LSTM model in the The PyTorch-Kaldi Speech Recognition Toolkit paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the Li-GRU model in the The PyTorch-Kaldi Speech Recognition Toolkit paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the Hierarchical maxout CNN + Dropout model in the paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the RNN model in the The PyTorch-Kaldi Speech Recognition Toolkit paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the GRU model in the The PyTorch-Kaldi Speech Recognition Toolkit paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the CNN in time and frequency + dropout, 17.6% w/o dropout model in the paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the Light Gated Recurrent Units model in the Light Gated Recurrent Units for Speech Recognition paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the RNN-CRF on 24(x3) MFSC model in the Segmental Recurrent Neural Networks for End-to-end Speech Recognition paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the Bi-RNN + Attention model in the Attention-Based Models for Speech Recognition paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the Bi-LSTM + skip connections w/ CTC model in the Speech Recognition with Deep Recurrent Neural Networks paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the QCNN-10L-256FM model in the Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the Soft Monotonic Attention (ours, offline) model in the Online and Linear-Time Attention by Enforcing Monotonic Alignments paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the LAS multitask with indicators sampling model in the Attention model for articulatory features detection paper on the TIMIT dataset? | Percentage error |
What metrics were used to measure the LSNN model in the Long short-term memory and learning-to-learn in networks of spiking neurons paper on the TIMIT dataset? | Percentage error |
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