DocumentCode :
353505
Title :
A segmental-feature HMM using parametric trajectory model
Author :
Yun, Young-Sun ; Oh, Yung-Hwan
Author_Institution :
Dept. of Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
1249
Abstract :
We present a parametric trajectory model for characterizing segmental features and their interaction within the segmental HMMs. The trajectory is obtained by applying the design matrix which includes transitional information on contiguous frames, and it is characterized as a polynomial regression function. To apply the trajectory to the segmental HMM, the extra- and intra-segmental variations are modified to contain the trajectory information. We made some experiments to examine the characteristics of variances and the variabilities in a segment. The experimental results are reported on the TIMIT corpus and performance is shown to improve significantly over that of the conventional HMM
Keywords :
hidden Markov models; polynomial matrices; speech recognition; TIMIT corpus; design matrix; extra-segmental variations; intra-segmental variations; parametric trajectory model; performance; polynomial regression function; segmental-feature HMM; transitional information; variabilities; variances; Computer science; Electronic mail; Estimation error; Hidden Markov models; Performance evaluation; Polynomials; Sampling methods; Speech; Symmetric matrices; Viterbi algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
Conference_Location :
Istanbul
ISSN :
1520-6149
Print_ISBN :
0-7803-6293-4
Type :
conf
DOI :
10.1109/ICASSP.2000.861802
Filename :
861802
Link To Document :
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