| target: | https://phonet.readthedocs.io/en/latest/?badge=latest |
|---|---|
| alt: | Documentation Status |
This toolkit compute posteriors probabilities of phonological classes from audio files for several groups of phonemes according to the mode and manner of articulation.
If you are not sure about what phonological classes are, have a look at this Phonological classes tutorial
Paper
The list of the phonological classes available and the phonemes that are activated for each phonological class are observed in the following Table
The list of the phonological classes available and the phonemes that are activated for each phonological class are observed in the following Table
| Phonological class | Phonemes |
|---|---|
| vocalic | /a/, /e/, /i/, /o/, /u/ |
| consonantal | /b/, /tS/, /d/, /f/, /g/, /x/, /k/, /l/, /ʎ/, /m/, /n/, /p/, /ɾ/, /r/, /s/, /t/ |
| back | /a/, /o/, /u/ |
| anterior | /e/, /i/ |
| open | /a/, /e/, /o/ |
| close | /i/, /u/ |
| nasal | /m/, /n/ |
| stop | /p/, /b/, /t/, /k/, /g/, /tS/, /d/ |
| continuant | /f/, /b/, /tS/, /d/, /s/, /g/, /ʎ/, /x/ |
| lateral | /l/ |
| flap | /ɾ/ |
| trill | /r/ |
| voiced | /a/, /e/, /i/, /o/, /u/, /b/, /d/, /l/, /m/, /n/, /r/, /g/, /ʎ/ |
| strident | /f/, /s/, /tS/ |
| labial | /m/, /p/, /b/, /f/ |
| dental | /t/, /d/ |
| velar | /k/, /g/, /x/ |
| pause | /sil/ |
From this repository:
git clone https://github.com/jcvasquezc/phonet cd phonet python setup.py
Supported features:
- Estimate probabilities of phonological classes for an audio file
Estimate the phonological classes using the BGRU models for an audio file or for a folder that contains audio files inside:
python phon=Phonet([phonclass]) get_phon_wav(self, audio_file, feat_file, plot_flag=True)
| Parameters | Description |
|---|---|
| audio_file | file audio (.wav) sampled at 16 kHz |
| feat_file | file (.csv) to save the posteriors for the phonological classes |
| phonclass | list of phonological classes to be evaluated The list of phonological classes include: "consonantal", "back", "anterior", "open", "close", "nasal", "stop", "continuant", "lateral", "flap", "trill", "voice", "strident", "labial", "dental", "velar", "pause", "vocalic" or "all" |
| plot_flag | True or False, whether you want plots of phonological classes or not |
| returns | It crates the feat_file with the estimation of the phonological classes for each time-frame of the audio file. |
If you want to train Phonet in your own language, or specific phonological classes that are not defined here, please refer to the folder train and follow the instructions there.
If you experienced problems with the Training process, please send me an email <juan.vasquez@fau.de>
Phonet is available for research purposes
If you use Phonet, please cite the following paper.
- @inproceedings{Vasquez-Correa2019,
- author={J. C. Vásquez-Correa and P. Klumpp and J. R. Orozco-Arroyave and E. N"oth}, title={{Phonet: A Tool Based on Gated Recurrent Neural Networks to Extract Phonological Posteriors from Speech}}, year=2019, booktitle={Proc. Interspeech 2019}, pages={549--553}, doi={10.21437/Interspeech.2019-1405}, url={http://dx.doi.org/10.21437/Interspeech.2019-1405}
}