DocumentCode :
1724368
Title :
Noise Robust Speech Features for Automatic Continuous Speech Recognition using Running Spectrum Analysis
Author :
OHNUKI, Kazunaga ; Takahashi, Wataru ; Yoshizawa, Shingo ; Miyanaga, Yoshikazu
Author_Institution :
Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo
fYear :
2008
Firstpage :
150
Lastpage :
153
Abstract :
In this report, new robust speech feature is introduced and applied for an automatic continuous speech recognition system. Using these features, the noise robust continuous speech recognition can be realized. The new running spectrum analysis (RSA) method is used in order to remove un-speech components over 15 Hz in modulation spectrum domain. Using RSA, speech features are emphasized for the design of tri-phone HMM where the tri-phone HMM is used in continuous speech recognition. In order to show the performance of the developed system, some comparisons with conventional one are given in experiments.
Keywords :
hidden Markov models; spectral analysis; speech recognition; RSA; automatic continuous speech recognition; frequency 15 Hz; hidden Markov models; modulation spectrum domain; noise robust speech features; running spectrum analysis; tri-phone HMM; Automatic speech recognition; Feature extraction; Hidden Markov models; Noise reduction; Noise robustness; Random access memory; Speech analysis; Speech enhancement; Speech recognition; Working environment noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications and Information Technologies, 2008. ISCIT 2008. International Symposium on
Conference_Location :
Lao
Print_ISBN :
978-1-4244-2335-4
Electronic_ISBN :
978-1-4244-2336-1
Type :
conf
DOI :
10.1109/ISCIT.2008.4700172
Filename :
4700172
Link To Document :
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