DocumentCode :
2693696
Title :
Unsupervised pronunciation grammar growing using knowledge-based and data-driven approaches
Author :
Huang, Chien-Lin ; Wu, Chung-Hsien ; Li, Haizhou ; Hsieh, Chia-Hsin ; Ma, Bin
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan
fYear :
2008
fDate :
June 23 2008-April 26 2008
Firstpage :
1097
Lastpage :
1100
Abstract :
This study presents a novel approach to unsupervised pronunciation grammar growing for non-native speech recognition. Unsupervised pronunciation grammar growing includes pronunciation variation graph construction and non-native grammar generation. Knowledge-based and data-driven approaches are considered for variation graph construction. The measurement of confidence and support is used for grammar selection. Experiments show that unsupervised pronunciation grammar growing is suitable for the improvement of non-native speech recognition.
Keywords :
grammars; graph theory; speech recognition; knowledge-based-data-driven approaches; nonnative speech recognition; unsupervised pronunciation grammar; variation graph construction; Automatic speech recognition; Computer science; Data engineering; Frequency; Hidden Markov models; Knowledge engineering; Man machine systems; Natural languages; Speech analysis; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2008 IEEE International Conference on
Conference_Location :
Hannover
Print_ISBN :
978-1-4244-2570-9
Electronic_ISBN :
978-1-4244-2571-6
Type :
conf
DOI :
10.1109/ICME.2008.4607630
Filename :
4607630
Link To Document :
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