Towards Improving the Intelligibility of Dysarthric Speech

Humans utilize many muscles to produce intelligible speech, including lips, face and throat. Dysarthria is a speech disorder that surfaces when one has weal muscles due to brain damage. Primary characteristics of a dysarthric patient are slurred and slow speech that can be difficult to understand based on the severity of the condition. This paper proposes an approach to improve the intelligibility of the dysarthric speech using a simple yet effective speech-transformation technique such as warping the frequency of LPC poles and mapping coefficients of linear predictive coding. This technique was applied to dysarthric audio from the UA-speech database to obtain the desired results. Both objective and subjective measures are used to evaluate the transformed speech. The obtained results pointed towards a significant improvement in the dysarthric speech’s intelligibility. This method can be used to develop special voice-enabled search platforms for dysarthric patients and in helping rehabilitation of the patients by developing a speech therapy based on auditory feedback.