DocumentCode :
3644765
Title :
Real-time large vocabulary spontaneous speech recognition for spoken dialog systems
Author :
Jan Švec;Luboš Šmídl
Author_Institution :
Center of Applied Cybernetics, Department of Cybernetics, University of West Bohemia, Pilsen, Czech Republic
Volume :
5
fYear :
2011
Firstpage :
2431
Lastpage :
2436
Abstract :
This paper describes the method for modifying the baseline speech recognition system to be suitable for a use in spoken dialog system with mixed initiative and natural user´s input. We present three approaches for extending the recognition vocabulary to ensure the spoken dialog system is able to recognize all entities in the given domain. The colloquial text normalization method is proposed. The experiments performed on spontaneous speech corpus suggested that the proposed method is very important for languages where the formal written language and a common colloquial speech are very different. The overall word error rate was reduced by 16.7%.
Keywords :
"Vocabulary","Hidden Markov models","Speech recognition","Training data","Speech","Data models","History"
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2011 4th International Congress on
Print_ISBN :
978-1-4244-9304-3
Type :
conf
DOI :
10.1109/CISP.2011.6100773
Filename :
6100773
Link To Document :
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