NDLI: Candidate expansion and prosody adjustment for natural speech synthesis using a small corpus

Content Provider	ACM Digital Library
Author	Wu, Chung-Hsien Chen, Yan-You Huang, Yi-Chin Lin, Shih-Lun Wang, Jhing-Fa
Copyright Year	2016
Abstract	This study proposes a hybrid approach to natural-sounding speech synthesis based on candidate expansion, unit selection, and prosody adjustment using a small corpus. The proposed method is more specific to tonal language, in particular Mandarin. In conventional speech synthesis studies, the quality of synthesized speech depends heavily on the size of the speech corpus. However, it is highly time-consuming and labor-intensive to prepare a large labeled corpus. In this work, candidate expansion is proposed to retrieve potential candidates that are unlikely to be retrieved using only linguistic features. The optimal unit sequence is then obtained from the expanded candidates by using the proposed unit selection mechanism at the phoneme and prosodic word levels. Finally, a prosodic word-level prosody adjustment is proposed to improve the continuity and smoothness of the prosody of the synthesized speech. To evaluate the proposed method, the Tsing-Hua corpus of speech synthesis was adopted. The results of an objective evaluation demonstrate the effectiveness of candidate expansion and the improvement of the continuity and smoothness of the prosody of the synthesized speech. The results of a subjective evaluation also show the proposed system could synthesize the speech with improved quality and naturalness, in particular for a small-sized or resource-limited corpus.
Starting Page	1052
Ending Page	1065
Page Count	14
File Format	PDF
ISSN	23299290
e-ISSN	23299304
Volume Number	24
Issue Number	6
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-06-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Articulatory features Candidate expansion Hybrid speech synthesis Prosody adjustment
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

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