Intelligibility Enhancement of Acoustic Noisy Speech for Autism Spectrum Disorder Condition

Author:

M. Pillonetto, A. Queiroz, R. Coelho

Keyword:

Electrical Engineering and Systems Science, Audio and Speech Processing, Audio and Speech Processing (eess.AS), Sound (cs.SD)

journal:

date:

2024-01-22 00:00:00

Abstract

This work introduces a time domain personalized method (pGTFF0) to achieve intelligibility improvement of noisy speech for Autism Spectrum Disorder (ASD) situation. For this proposal, harmonic features estimated from speech frames are considered as center frequencies of Gammatone auditory filterbanks. A gain factor is further applied to the output of the filtered samples. The key goal is the emulation of an external noise filtering tailored for individuals with ASD. A perceptual listening test demonstrates that ASD volunteers attained lower intelligibility rates than Neurotypical (NT). The proposed solution is compared to three competing approaches considering four acoustic noises at different signal-to-noise ratios. Two objective measures (ESTOI and PESQ) are also adopted for evaluation. The experimental results show that the personalized solution outperformed the competing approaches in terms of intelligibility and quality improvement.

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