Awesome
TorchAudio Ruby
:fire: An audio library for Torch.rb
Installation
First, install SoX. For Homebrew, use:
brew install sox
Add this line to your application’s Gemfile:
gem "torchaudio"
Getting Started
This library follows the Python API. Many methods and options are missing at the moment. PRs welcome!
Tutorial
Download the audio file and install the matplotlib gem first.
Basics
Load a file
waveform, sample_rate = TorchAudio.load("file.wav")
Save a file
TorchAudio.save("new.wave", waveform, sample_rate)
Transforms
TorchAudio::Transforms::Spectrogram.new.call(waveform)
Supported transforms are:
- AmplitudeToDB
- ComputeDeltas
- Fade
- MelScale
- MelSpectrogram
- MFCC
- MuLawDecoding
- MuLawEncoding
- Spectrogram
- Vol
Functional
TorchAudio::Functional.lowpass_biquad(waveform, sample_rate, cutoff_freq)
Supported functions are:
- amplitude_to_DB
- compute_deltas
- create_dct
- create_fb_matrix
- DB_to_amplitude
- dither
- gain
- highpass_biquad
- lowpass_biquad
- mu_law_decoding
- mu_law_encoding
- spectrogram
Datasets
Load a dataset
TorchAudio::Datasets::YESNO.new(".", download: true)
Supported datasets are:
Disclaimer
This library downloads and prepares public datasets. We don’t host any datasets. Be sure to adhere to the license for each dataset.
If you’re a dataset owner and wish to update any details or remove it from this project, let us know.
SoX Installation
Mac
brew install sox
Windows
todo
Ubuntu
sudo apt install sox libsox-dev libsox-fmt-all
Travis CI
Add to .travis.yml:
addons:
apt:
packages:
- sox
- libsox-dev
- libsox-fmt-all
History
View the changelog
Contributing
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- Report bugs
- Fix bugs and submit pull requests
- Write, clarify, or fix documentation
- Suggest or add new features
To get started with development:
git clone https://github.com/ankane/torchaudio-ruby.git
cd torchaudio-ruby
bundle install
bundle exec rake compile
bundle exec rake test