In this work, we study the variations in the time and frequency domains inside a Spanish language corpus of speakers with non-pathological and pathological speech. We show how pathological speech has a greater variability in the duration of the words than non-pathological speech, while in the frequency domain we show that the vowels confusability increases by a 18%. The baseline experiments in Automatic Speech Recognition (ASR) with this corpus demonstrate that this variability causes a loss in the performance of ASR systems. To reduce the impact of time and frequency variability we use a recent Vocal Tract Length Normalization (VTLN) system: MATE (augMented stAte space acousTic modEl), as a way of improving the performance of ASR systems when dealing with speakers who suffer any kind of speech pathology. Experiments with MATE show a 17.04% and 11.19% WER reduction by using frequency and time MATE respectively.
Cite as: Saz, O., Miguel, A., Lleida, E., Ortega, A., Buera, L. (2006) Study of time and frequency variability in pathological speech and error reduction methods for automatic speech recognition. Proc. Interspeech 2006, paper 1266-Tue1FoP.11, doi: 10.21437/Interspeech.2006-317
@inproceedings{saz06_interspeech,
author={Oscar Saz and Antonio Miguel and Eduardo Lleida and Alfonso Ortega and Luis Buera},
title={{Study of time and frequency variability in pathological speech and error reduction methods for automatic speech recognition}},
year=2006,
booktitle={Proc. Interspeech 2006},
pages={paper 1266-Tue1FoP.11},
doi={10.21437/Interspeech.2006-317}
}