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 [BibTeX] [Marc21]
Utterance Verification-based Dysarthric Speech Intelligibility Assessment using Phonetic Posterior Features
Type of publication: Journal paper
Citation: Fritsch_IEEESPL_2021
Publication status: Accepted
Journal: IEEE Signal Processing Letters
Volume: 28
Year: 2021
Pages: 224 - 228
ISSN: 1558-2361
DOI: 10.1109/LSP.2021.3050362
Abstract: In the literature, the task of dysarthric speech intel-ligibility assessment has been approached through development of different low-level feature representations, subspace model-ing, phone confidence estimation or measurement of automatic speech recognition system accuracy. This paper proposes a novel approach where the intelligibility is estimated as the percentage of correct words uttered by a speaker with dysarthria by matching and verifying utterances of the speaker with dysarthria against control speakers' utterances in phone posterior feature space and broad phonetic posterior feature space. Experimental validation of the proposed approach on the UA-Speech database, with posterior feature estimators trained on the data from auxiliary domain and language, obtained a best Pearson's correlation coefficient (r) of 0.950 and Spearman's correlation coefficient (ρ) of 0.957. Furthermore, replacing control speakers' speech with speech synthesized by a neural text-to-speech system obtained a best r of 0.931 and ρ of 0.961.
Keywords: Dysarthric speech, Objective intelligibility Assessment, Posterior features, utterance verification
Projects TAPAS
Authors Fritsch, Julian
Magimai.-Doss, Mathew
Added by: [UNK]
Total mark: 0
  • Fritsch_IEEESPL_2021.pdf