ASRdys is a Kaldi recipe to build an ASR for speakers with dysarthria. The recipe works on the Torgo database [1] so you need to obtain this data first and include its location into the path.sh file. Several models are used in the pipeline implemented in run.sh/runMultipleSubtests.sh.
To train several models on all the speakers except one for testing do:
bash ./run.sh <test_speaker>where <test_speaker> is one of the 15 speakers in the database.
To train several models on 15 different configurations taking a different test speaker at a time do:
bash ./runAllTests.shTo train several models and see the results in different partions of the test set define those partitions with torgo_data_prep_multiple_tests.sh (if different to the current ones), initialise the tests variable in runMultipleSubtests.sh and do as before:
bash ./runMultipleSubtests.sh <test_speaker>Remember to adapt path.sh to your necessities.
Update the Deep Learning scripts
Add a RESULTS file
Cristina España-Bonet
(especific scripts only for the Torgo database: ./local)
Cristina España-Bonet and José A. R. Fonollosa Automatic Speech Recognition with Deep Neural Networks for Impaired Speech Chapter in Advances in Speech and Language Technologies for Iberian Languages, part of the series Lecture Notes in Artificial Intelligence. In A. Abad et al. (Eds.). IberSPEECH 2016, LNAI 10077, Chapter 10, pages 97-107, October 2016.
[1] Frank Rudzicz, Aravind Kumar Namasivayam and Talya Wolff. The TORGO database of acoustic and articulatory speech from speakers with dysarthria. Language Resources and Evaluation, December 2012, Volume 46, Issue 4, pp 523-541