uiuc-sst/pseudo-swahili

Kaldi ASR for Swahili, using almost no Swahili resources. # Pseudo-Swahili ASR for Kaldi Uses almost no Swahili resources. Audio FSTs are trained from Voxforge's English. ### Prerequisites - The shell commands `flac`, `gawk`, `swig`, and `wget`. On Ubuntu, you might need to `sudo apt install flac gawk swig wget`. - The Kaldi toolkit for automatic speech recognition. To install it, `git clone github.com`. - The SRI Language Modeling Toolkit. To add this to Kaldi, download the file `srilm.tgz` into `kaldi/tools`, and then (from `kaldi/tools`) `./install_srilm.sh`. - The Sequitur grapheme-to-phoneme converter. To add this to Kaldi, `cd kaldi/tools && extras/install_sequitur.sh`. (You might first need to `sudo pip install numpy` (for Python 2.7)). ### Usage Add these pseudo-Swahili scripts to Kaldi. ``` cd kaldi/egs git clone github.com cd pseudo-swahili/s5 ln -s ../../wsj/s5/steps steps ln -s ../../wsj/s5/utils utils ``` Get the Voxforge corpus of spoken English (this takes 45 minutes, and uses 25 GB of disk space). `./getdata.sh` Build the low-resource language model, vocabulary, etc. for Swahili. `cd pseudo-swahili/pseudo && ./a.sh` Build and test the speech recognizer. `cd pseudo-swahili/s5 && ./run.sh`