DocumentCode :
1133476
Title :
ASR in mobile phones - an industrial approach
Author :
Varga, Imre ; Aalburg, Stefanie ; Andrassy, Bernt ; Astrov, Sergey ; Bauer, Josef G. ; Beaugeant, Christophe ; Geissler, C. ; Höge, Harald
Author_Institution :
Siemens AG, Munich, Germany
Volume :
10
Issue :
8
fYear :
2002
fDate :
11/1/2002 12:00:00 AM
Firstpage :
562
Lastpage :
569
Abstract :
In order to make hidden Markov model (HMM) speech recognition suitable for mobile phone applications, Siemens developed a recognizer, Very Smart Recognizer (VSR), for deployment in future mobile phone generations. Typical applications will be name dialling, command and control operations suited for different environments, for example in cars. The paper describes research and development issues of a speech recognizer in mobile devices focusing on noise robustness, memory efficiency and integer implementation. The VSR is shown to reach a word error rate as low as 4.1% on continuous digits recorded in a car environment. Furthermore by means of discriminative training and HMM-parameter coding, the memory requirements of the VSR HMMs are smaller than 64 kBytes.
Keywords :
hidden Markov models; mobile handsets; speech recognition; DSP implementation; HMM-parameter coding; Siemens; Very Smart Recognizer; automatic speech recognition; cars; command and control; discriminative training; hidden Markov model; integer implementation; memory efficiency; memory requirements; mobile devices; mobile phones; name dialling; noise robustness; research and development; word error rate; Automatic speech recognition; Command and control systems; Error analysis; Hidden Markov models; Mobile handsets; Noise robustness; Research and development; Speech enhancement; Speech recognition; Working environment noise;
fLanguage :
English
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6676
Type :
jour
DOI :
10.1109/TSA.2002.804548
Filename :
1175528
Link To Document :
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