https://github.com/bootphon/abnet3

Siamese network for unsupervised speech representation learning

https://github.com/bootphon/abnet3

Keywords

Repository

Siamese network for unsupervised speech representation learning

https://github.com/bootphon/abnet3/blob/master/

# ABnet3

Representation learning package using side information, system for subword modeling for [Zeroresource challenge](http://sapience.dec.ens.fr/bootphon/2017/index.html).

### Overview



Build Representation for speech frames based on side information. Composed of different modules :

* `model.py`
* `loss.py`
* `sampler.py`
* `trainer.py`
* `embedder.py`
* `utils.py`
* `features.py`

### Installation of the package

#### Using conda

To install the ABnet3 package, you can use Anaconda, and either create a conda environment:

    conda env create --name abnet3 python=3.6 -f environment.yml

or use a conda environment you already have with python 3 :
    conda env update -f environment.yml

To install with GPU support (replace cuda75 with your version of cuda)

    conda install  pytorch=0.2 cuda75 -c pytorch

#### Using pip

- install the version 0.2.0 of pytorch for your hardware (http://pytorch.org/previous-versions/)

- install the pip packages : `pip install -r requirements.txt`
Once all the necessary packages are installed, simply launch:

#### Run abnet3 installation

    python setup.py build && python setup.py install

If you want to work on ABnet3 and develop your own modules, instead of:

    python setup.py install

you can launch:

    python setup.py develop

### Tensorboard vizualisation

The package tensorboardX needs to be installed to train the model: `pip install tensorboardX`.

The package will save train / dev loss during training. To vizualise them :

- Install tensorboard (`conda install tensorflow tensorflow-tensorboard`)

- run `tensorboard --logdir path/to/logdir`.
The default logdir is `./run` in the current directory.

### Documentation

You can see examples for running the gridsearch and replicating our results
in the repository https://github.com/Rachine/sampling_siamese2018

The cli documentation is here https://coml.lscp.ens.fr/git/Rachine/abnet3/src/master/gridsearch.md

### Tests

The package comes with a unit-tests suit. To run it, first install *pytest* on your Python environment:

    pip install pytest
    pytest test/

#### References

    .. [1] Riad, R., Dancette, C., Karadayi, J., Zeghidour, N., Schatz, T., Dupoux, E.
           *Sampling strategies in Siamese Networks for unsupervised speech representation learning.*
           In Nineteenth Annual Conference of the International Speech Communication Association

    .. [2] Thiolliere, R., Dunbar, E., Synnaeve, G., Versteegh, M., & Dupoux, E.
           *A hybrid dynamic time warping-deep neural network architecture for unsupervised acoustic modeling.*
           In Sixteenth Annual Conference of the International Speech Communication Association

    .. [3] Zeghidour, N., Synnaeve, G., Usunier, N. & Dupoux, E.
           *Joint Learning of Speaker and Phonetic Similarities with Siamese Networks.*
           In: INTERSPEECH-2016, (pp 1295-1299)



### Acknowledgments
A part of the code is inspired from the previous version in Theano of  [ABnet](https://github.com/bootphon/abnet2), and the [examples in Pytorch](https://github.com/pytorch/examples)

Owner

GitHub Events

Committers

Last synced: 9 months ago

Issues and Pull Requests

Last synced: 9 months ago