---
license: cc0-1.0
task_categories:
- automatic-speech-recognition
language:
- en
- de
- fr
- it
- ru
- es
tags:
- speech
- phonetics
- phoneme-recognition
- acoustic-modeling
pretty_name: Common Phone
size_categories:
- 10K<n<100K
---
# Dataset Card for Common Phone

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.
The current version of Common Phone comprises 116,5 hours of speech samples, collected from 11.246 speakers in 6 languages.

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.

It also served as a foundation for highly robust production-grade speech and phoneme recognition models.

## Dataset Details

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.

If you use Common Phone for your research, please cite our work:
```
 @inproceedings{
  klumpp2022common,
  title={Common Phone: A Multilingual Dataset for Robust Acoustic Modelling},
  author={Klumpp, Philipp and Arias, Tomas and P{\'e}rez-Toro, Paula Andrea and Noeth, Elmar and Orozco-Arroyave, Juan},
  booktitle={Proceedings of the Thirteenth Language Resources and Evaluation Conference},
  pages={763--768},
  year={2022}
}
```

- **Curated by: [Philipp Klumpp](https://www.linkedin.com/in/philipp-klumpp/)**
- **Language(s) (NLP): English, German, Italian, Spanish, French, Russian**
- **License: Creative Commons Zero v1.0 Universal**

### Dataset Sources

The dataset sources, including mp3/wav files and TextGrids, are also available via Zenodo.

- **Repository: [Common Phone on Zenodo](https://zenodo.org/records/5846137)**

## Uses

**Why Common Phone?**
  - Large number of speakers and varying acoustic conditions to improve robustness of ML models
  - Time-aligned IPA phonetic transcription for every audio sample
  - Gender-balanced and age-group-matched (equal number of female/male speakers in every age group)
  - Support for six different languages to leverage multi-lingual approaches
  - Original MP3 files plus standard WAVE files


### Source Data

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).

### Annotations

Common Phone provides automatically generated phonetic annotation with alignment for each spoken text sample.