DocumentCode :
394292
Title :
An efficient text analyzer with prosody generator-driven approach for Mandarin text-to-speech
Author :
Hwang, Shaw-Hwa ; Yeh, Cheng-Yu
Author_Institution :
Dept. of Electr. Eng., Nat. Taipei Univ. of Technol., Taiwan
Volume :
1
fYear :
2003
fDate :
6-10 April 2003
Abstract :
A new approach for an efficient text analyzer is proposed. The prosody generator driven method is employed to design an efficient text analyzer for Mandarin text-to-speech synthesis. Three heuristic and theoretical methods are used to examine the capability of each linguistic feature. Firstly, the contribution of each linguistic feature on the prosody generator is examined experimentally. Secondly, the cross-influence of each linguistic feature on the prosody generator is analyzed. Thirdly, the problem of over- and under-classification on the linguistic feature is inspected. Finally, these three analytic results are referenced to design an efficient text analyzer. More than 39103 Chinese characters are employed to examine the performance of our text analyzer. Less than 78 ms is needed for word tagging under a P4 1.4 GHz PC. The correction rate with 97% is achieved. It confirms that the performance of our text analyzer is very good. Moreover, more natural and fluent speech is obtained under the lower computation.
Keywords :
feature extraction; linguistics; signal classification; speech synthesis; text analysis; Chinese characters; Mandarin text-to-speech synthesis; efficient text analyzer; heuristic methods; linguistic feature; over-classification; performance; prosody generator; under-classification; Data mining; Degradation; Electronic mail; Energy resolution; Feature extraction; Natural languages; Performance analysis; Speech analysis; Speech synthesis; Tagging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-7663-3
Type :
conf
DOI :
10.1109/ICASSP.2003.1198824
Filename :
1198824
Link To Document :
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