Audio library for Torch-7
- Support audio I/O (Load files)
- Common audio operations (Short-time Fourier transforms, Spectrograms)
Load the following formats into a torch Tensor
- mp3, wav, aac, ogg, flac, avr, cdda, cvs/vms,
- aiff, au, amr, mp2, mp4, ac3, avi, wmv,
- mpeg, ircam and any other format supported by libsox.
Calculate Short-time Fourier transforms with
- window types - rectangular, hamming, hann, bartlett
Generate spectrograms
- libsox v14.3.2 or above
- libfftw3
Quick install on OSX (Homebrew):
$ brew install sox
$ brew install fftwLinux (Ubuntu):
$ sudo apt-get install libfftw3-dev
$ sudo apt-get install sox libsox-dev libsox-fmt-allThis project can be installed with luarocks like this:
$ luarocks install https://raw.githubusercontent.com/soumith/lua---audio/master/audio-0.1-0.rockspecOn Ubuntu 13.04 64-bit, I had to modify the command slightly because of new library directory structures not picked up by luarocks.
$ sudo luarocks install https://raw.githubusercontent.com/soumith/lua---audio/master/audio-0.1-0.rockspec LIBSOX_LIBDIR=/usr/lib/x86_64-linux-gnu/ LIBFFTW3_LIBDIR=/usr/lib/x86_64-linux-gnuOr, if you have downloaded this repository on your machine, and you are in its directory:
$ luarocks makeaudio.load
loads an audio file into a torch.Tensor
usage:
audio.load(
string -- path to file
)
audio.stft
calculate the stft of an audio. returns a 3D tensor, with number_of_windows x window_size/2+1 x 2(complex number with real and complex parts)
usage:
audio.stft(
torch.Tensor -- input single-channel audio
number -- window size
string -- window type: rect, hamming, hann, bartlett
number -- stride
)
audio.spectrogram
generate the spectrogram of an audio. returns a 2D tensor, with number_of_windows x window_size/2+1, each value representing the magnitude of each frequency in dB
usage:
audio.spectrogram(
torch.Tensor -- input single-channel audio
number -- window size
string -- window type: rect, hamming, hann, bartlett
number -- stride
)
Generate a spectrogram
require 'audio'
require 'image' -- to display the spectrogram
voice = audio.samplevoice()
spect = audio.spectrogram(voice, 8192, 'hann', 512)
image.display(spect)