ARTICLE Fritsch_IEEESPL_2021/IDIAP Utterance Verification-based Dysarthric Speech Intelligibility Assessment using Phonetic Posterior Features Fritsch, Julian Magimai.-Doss, Mathew Dysarthric speech Objective intelligibility Assessment Posterior features utterance verification EXTERNAL http://publications.idiap.ch/attachments/papers/2021/Fritsch_IEEESPL_2021.pdf PUBLIC IEEE Signal Processing Letters 28 224 - 228 1558-2361 2021 10.1109/LSP.2021.3050362 doi 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.