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ID 57782
FullText URL
Author
Murakami, Hiroki Okayama University
Contributor
Sunao Hara Okayama University ORCID Kaken ID publons researchmap
Masanobu Abe Okayama University
Abstract
In this paper, we propose using phonemic information in addition to acoustic features to improve the intelligibility of speech uttered by patients with articulation disorders caused by a wide glossectomy. Our previous studies showed that voice conversion algorithm improves the quality of glossectomy patients' speech. However, losses in acoustic features of glossectomy patients' speech are so large that the quality of the reconstructed speech is low. To solve this problem, we explored potentials of several additional information to improve speech intelligibility. One of the candidates is phonemic information, more specifically Phoneme Labels as Auxiliary input (PLA). To combine both acoustic features and PLA, we employed a DNN-based algorithm. PLA is represented by a kind of one-of-k vector, i.e., PLA has a weight value (<; 1.0) that gradually changes in time axis, whereas one-of-k has a binary value (0 or 1). The results showed that the proposed algorithm reduced the mel-frequency cepstral distortion for all phonemes, and almost always improved intelligibility. Notably, the intelligibility was largely improved in phonemes /s/ and /z/, mainly because the tongue is used to sustain constriction to produces these phonemes. This indicates that PLA works well to compensate the lack of a tongue.
Published Date
2019-11
Publication Title
Proceedings of APSIPA Annual Summit and Conference
Volume
volume2019
Publisher
IEEE
Start Page
138
End Page
142
ISSN
2640-009X
Content Type
Conference Paper
language
英語
Copyright Holders
© Copyright APSIPA
Event Title
APSIPA Annual Summit and Conference
Event Location
Lanzhou, China
Event Dates
18-21 Nov. 2019
File Version
publisher
Refereed
True