DocumentCode
737697
Title
Study on the consistency analysis between the prosody and the spectrum for Mandarin speech
Author
Cheng-Yu Yeh ; Kuan-Lin Chen ; Shaw-Hwa Hwang ; Long-Jhe Yan
Author_Institution
Dept. of Electr. Eng., Nat. Chin-Yi Univ. of Technol., Taichung, Taiwan
Volume
7
Issue
2
fYear
2013
fDate
4/1/2013 12:00:00 AM
Firstpage
158
Lastpage
165
Abstract
In this work, a consistency analysis between the prosody and the spectrum for Mandarin speech is presented. Found by an inspection on the pronunciation process of human beings, the consistency can be interpreted as a close correlated relation of a warping curve between the spectrum and the prosody intra a syllable. Through three steps in the procedure of the consistency analysis, the hidden Markov model (HMM) algorithm is used firstly to decode HMM-state sequences within a syllable at the same time as to divide them into three segments. Secondly, based on a designated syllable, the vector quantisation (VQ) with the Linde-Buzo-Gray algorithm is used to train the VQ codebooks of each segment. Thirdly, the prosodic vector of each segment is encoded as an index by VQ codebooks, and then the probability of each possible path is evaluated as a prerequisite to analyse the consistency. It is demonstrated experimentally that a consistency is definitely acquired in case the syllable is located exactly in the same word. These results offer a research direction that the warping process between the spectrum and the prosody intra a syllable must be considered in a text-to-speech system to improve the speech quality.
Keywords
hidden Markov models; speech processing; vector quantisation; HMM state sequences; Linde Buzo Gray algorithm; Mandarin speech quality; VQ codebooks; consistency analysis; hidden Markov model algorithm; pronunciation process; prosodic vector; prosody; text to speech system; vector quantisation; warping curve; warping process;
fLanguage
English
Journal_Title
Signal Processing, IET
Publisher
iet
ISSN
1751-9675
Type
jour
DOI
10.1049/iet-spr.2012.0099
Filename
6545033
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