Perceptually Enhanced Single Frequency Filtering for Dysarthric Speech Detection and Intelligibility Assessment

This paper proposes a new speech feature representation that improves the intelligibility assessment of dysarthric speech. The formulation of the feature set is motivated from the human auditory perception and high time-frequency resolution property of single frequency filtering (SFF) technique. The...

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Bibliographic Details
Main Authors: Gurugubelli, Krishna, Vuppala, Anil Kumar
Format: Conference Proceeding
Language:English
Subjects:
Auditory perception
Dysarthria detection
Feature extraction
Intelligibility assessment
Mel frequency cepstral coefficient
Signal resolution
Single frequency filtering
Time-frequency analysis
Voice activity detection
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Summary:This paper proposes a new speech feature representation that improves the intelligibility assessment of dysarthric speech. The formulation of the feature set is motivated from the human auditory perception and high time-frequency resolution property of single frequency filtering (SFF) technique. The proposed features are named as perceptually enhanced single frequency cepstral coefficients (PE-SFCC). As a part of SFF technique implementation, speech signal passed through a single pole complex bandpass filter bank to obtain high-resolution time-frequency distribution. Then, the distribution is enhanced by using a set of auditory perceptual operators. Lastly, traditional homomorphic analysis has been carried out on the resulting signal to obtain PE-SFCC feature vector. The performance of proposed features in dysarthric speech detection and its intelligibility assessment has been reported on UASPEECH database. The PE-SFCC features outperformed the state-of-the-art features in dysarthric speech detection and intelligibility assessment.
ISSN:2379-190X
DOI:10.1109/ICASSP.2019.8683314