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--- |
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license: cc0-1.0 |
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task_categories: |
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- automatic-speech-recognition |
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language: |
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- en |
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- de |
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- fr |
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- it |
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- ru |
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- es |
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tags: |
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- speech |
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- phonetics |
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- phoneme-recognition |
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- acoustic-modeling |
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pretty_name: Common Phone |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Dataset Card for Common Phone |
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This corpus aims to provide a basis for Machine Learning (ML) researchers and enthusiasts to train and test their models against a wide variety of speakers, hardware/software ecosystems and acoustic conditions to improve generalization and availability of ML in real-world speech applications. |
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The current version of Common Phone comprises 116,5 hours of speech samples, collected from 11.246 speakers in 6 languages. |
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Common Phone has been used as the primary corpus for the PhD thesis of Philipp Klumpp: [Phonetic Transfer Learning from Healthy References for the Analysis of Pathological Speech](https://www.researchgate.net/publication/382194988_Phonetic_Transfer_Learning_from_Healthy_References_for_the_Analysis_of_Pathological_Speech). The respective [Wav2Vec2 model](https://huggingface.co/pklumpp/Wav2Vec2_CommonPhone) can also be found on Hugging Face. |
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It also served as a foundation for highly robust production-grade speech and phoneme recognition models. |
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## Dataset Details |
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For details, check out our peer-reviewed publication [Common Phone: A Multilingual Dataset for Robust Acoustic Modelling](https://arxiv.org/abs/2201.05912), which was presented at LREC 2022. |
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If you use Common Phone for your research, please cite our work: |
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``` |
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@inproceedings{ |
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klumpp2022common, |
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title={Common Phone: A Multilingual Dataset for Robust Acoustic Modelling}, |
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author={Klumpp, Philipp and Arias, Tomas and P{\'e}rez-Toro, Paula Andrea and Noeth, Elmar and Orozco-Arroyave, Juan}, |
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booktitle={Proceedings of the Thirteenth Language Resources and Evaluation Conference}, |
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pages={763--768}, |
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year={2022} |
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} |
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``` |
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- **Curated by: [Philipp Klumpp](https://www.linkedin.com/in/philipp-klumpp/)** |
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- **Language(s) (NLP): English, German, Italian, Spanish, French, Russian** |
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- **License: Creative Commons Zero v1.0 Universal** |
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### Dataset Sources |
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The dataset sources, including mp3/wav files and TextGrids, are also available via Zenodo. |
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- **Repository: [Common Phone on Zenodo](https://zenodo.org/records/5846137)** |
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## Uses |
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**Why Common Phone?** |
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- Large number of speakers and varying acoustic conditions to improve robustness of ML models |
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- Time-aligned IPA phonetic transcription for every audio sample |
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- Gender-balanced and age-group-matched (equal number of female/male speakers in every age group) |
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- Support for six different languages to leverage multi-lingual approaches |
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- Original MP3 files plus standard WAVE files |
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### Source Data |
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Common Phone was derived from Common Voice, revision 7.0. More information can be found on the project's [website](https://commonvoice.mozilla.org/de). |
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### Annotations |
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Common Phone provides automatically generated phonetic annotation with alignment for each spoken text sample. |
