Browsing by Author "Kuo, Chin-Kuan"

Now showing 1 - 2 of 2

A SYLLABLE-BASED PROSODY MODELING FOR L1 AND L2 ENGLISH SPEECHES
(2012)
Chen, Wei-Fan
;
Kuo, Chin-Kuan
;
Wang, Yih-Ru
;
Chen, Sin-Horng
;
電機工程學系
In this paper, a statistical prosody modeling approach for L1 and L2 English speeches is proposed. The study focuses on the modeling of two prosodic-acoustic features: syllable duration and log-pitch contour. Several major affecting factors (AFs) that influence the variations of these two features are considered. They include lexical stress, word length, nearby break type, phonemic constituent of syllable, and prosodic state. A sequential optimization procedure is adopted to automatically train the two models from the TWNAESOP corpus recorded in Taiwan. Experimental results showed that most AFs estimated agreed well with our prior linguistic knowledge. The differences in the prosody of L1 and L2 speeches were also explored.
Hierarchical Prosody Modeling of English Speech and its Application to TTS
(2014-01-01)
Tsai, Chung-Yao
;
Kuo, Chin-Kuan
;
Wang, Yih-Ru
;
Chen, Sin-Horng
;
Liao, I-Bin
In this paper, a hierarchical prosody modeling approach for English speech is proposed. It is an extended version of the HPM approach proposed previously for Mandarin speech. It first designs a syllable-based, statistical prosodic model to describe various relationships of prosodic-acoustic features of the speech signal, linguistic features of the associated text, and prosodic tags representing the underlining prosody structure of the speech. It then employs a prosody labeling and modeling algorithm to estimate the model parameters and label the prosodic tags of all training utterances simultaneously from a prosody-unlabeled speech corpus. Experimental results on a corpus containing many paragraphic utterances of a female English-majored Chinese speaker show that the inferred parameters of the model are all meaningful. We then use the trained model to generate prosodic information for a TTS system. An informal listening test shows that the synthetic speech sounds quite natural.