DocumentCode
2066317
Title
Recognition of Syllable-Contracted Words in Spontaneous Speech Using Word Expansion and Duration Information
Author
Liang, Wei-Bin ; Wu, Chung-Hsien ; Kang, Yu-Kai
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
fYear
2008
fDate
16-19 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
This paper presents a graphical model-based approach to syllable-contracted (SC) word recognition of spontaneous Mandarin speech. Phone deletion and pronunciation reduction are two major effects for the syllable-contracted words in spontaneous speech. In this study, the syllable- contracted (SC) words selected from a collected corpus are used for pronunciation lexicon expansion to deal with the phone deletion problem. The duration information of SC words is then incorporated to cover the effect of pronunciation reduction. The graphical model is employed to rescore all possible word sequences, including the expanded SC words, to obtain the final word sequence. In the experimental results, the Mandarin Conversional Dialogue Corpus (MCDC) was used to evaluate the proposed method. Compared with the previous work, a satisfactory improvement on the performance of the proposed approach can be achieved.
Keywords
speech recognition; Mandarin conversional dialogue corpus; duration information; graphical model-based approach; phone deletion problem; pronunciation lexicon expansion; pronunciation reduction; spontaneous Mandarin speech; syllable-contracted word recognition; syllable-contracted words recognition; word expansion; Acoustic measurements; Automatic speech recognition; Computer science; Decision trees; Graphical models; High performance computing; Humans; Predictive models; Speech recognition; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Chinese Spoken Language Processing, 2008. ISCSLP '08. 6th International Symposium on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2942-4
Electronic_ISBN
978-1-4244-2943-1
Type
conf
DOI
10.1109/CHINSL.2008.ECP.68
Filename
4730322
Link To Document