Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/gooofy/py-kaldi-asr
Some simple wrappers around kaldi-asr intended to make using kaldi's (online) decoders as convenient as possible.
https://github.com/gooofy/py-kaldi-asr
asr kaldi kaldi-asr python python-2 speech-recognition wrapper
Last synced: about 1 month ago
JSON representation
Some simple wrappers around kaldi-asr intended to make using kaldi's (online) decoders as convenient as possible.
- Host: GitHub
- URL: https://github.com/gooofy/py-kaldi-asr
- Owner: gooofy
- License: apache-2.0
- Created: 2016-11-25T21:25:59.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2021-02-23T12:59:36.000Z (over 3 years ago)
- Last Synced: 2024-10-07T22:17:19.241Z (about 1 month ago)
- Topics: asr, kaldi, kaldi-asr, python, python-2, speech-recognition, wrapper
- Language: C++
- Size: 491 KB
- Stars: 170
- Watchers: 20
- Forks: 56
- Open Issues: 17
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# py-kaldi-asr
Some simple wrappers around kaldi-asr intended to make using kaldi's online nnet3-chain
decoders as convenient as possible. Kaldi's online GMM decoders are also supported.
Target audience are developers who would like to use kaldi-asr as-is for speech
recognition in their application on GNU/Linux operating systems.
Constructive comments, patches and pull-requests are very welcome.
Getting Started
===============
We recommend using pre-trained modules from the [zamia-speech](http://zamia-speech.org/) project
to get started. There you will also find a tutorial complete with links to pre-built binary packages
to get you up and running with free and open source speech recognition in a matter of minutes:
[Zamia Speech Tutorial](https://github.com/gooofy/zamia-speech#get-started-with-our-pre-trained-models)
Example Code
------------
Simple wav file decoding:
```python
from kaldiasr.nnet3 import KaldiNNet3OnlineModel, KaldiNNet3OnlineDecoder
MODELDIR = 'data/models/kaldi-generic-en-tdnn_sp-latest'
WAVFILE = 'data/dw961.wav'
kaldi_model = KaldiNNet3OnlineModel (MODELDIR)
decoder = KaldiNNet3OnlineDecoder (kaldi_model)
if decoder.decode_wav_file(WAVFILE):
s, l = decoder.get_decoded_string()
print
print u"*****************************************************************"
print u"**", WAVFILE
print u"**", s
print u"** %s likelihood:" % MODELDIR, l
print u"*****************************************************************"
print
else:
print "***ERROR: decoding of %s failed." % WAVFILE
```
Please check the examples directory for more example code.
Requirements
============
* Python 2.7 or 3.5+
* NumPy
* Cython
* [kaldi-asr](http://kaldi-asr.org/ "kaldi-asr.org")
Setup Notes
===========
Source
------
At the time of this writing kaldi-asr does not seem to have an official way to
install it on a system.
So, for now we will rely on pkg-config to provide LIBS and CFLAGS for compilation:
Create a file called `kaldi-asr.pc` somewhere in your `PKG_CONFIG_PATH` that provides
this information - here is what such a file could look like (details depend on your OS environment):
```bash
kaldi_root=/opt/kaldi
Name: kaldi-asr
Description: kaldi-asr speech recognition toolkit
Version: 5.2
Requires: atlas
Libs: -L${kaldi_root}/tools/openfst/lib -L${kaldi_root}/src/lib -lkaldi-decoder -lkaldi-lat -lkaldi-fstext -lkaldi-hmm -lkaldi-feat -lkaldi-transform -lkaldi-gmm -lkaldi-tree -lkaldi-util -lkaldi-matrix -lkaldi-base -lkaldi-nnet3 -lkaldi-online2 -lkaldi-cudamatrix -lkaldi-ivector -lfst
Cflags: -I${kaldi_root}/src -I${kaldi_root}/tools/openfst/include
```
make sure `kaldi_root` points to wherever your kaldi checkout lives in your filesystem.
ATLAS
-----
You may need to install ATLAS headers even if you didn't need them to compile Kaldi.
```
$ sudo apt install libatlas-dev
```
License
=======
My own code is Apache licensed unless otherwise noted in the script's copyright
headers.
Some scripts and files are based on works of others, in those cases it is my
intention to keep the original license intact. Please make sure to check the
copyright headers inside for more information.
Author
======
Guenter Bartsch
Kaldi 5.1 adaptation contributed by mariasmo https://github.com/mariasmo
Kaldi GMM model support contributed by David Zurow https://github.com/daanzu
Python > 3.5 support contributed by Jakob Kruse https://github.com/jakob1111996