VLSI Architecture of GMM Processing and Viterbi Decoder for 60,000-Word Real-Time Continuous Speech Recognition
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概要
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We propose a low-memory-bandwidth, high-efficiency VLSI architecture for 60-k word real-time continuous speech recognition. Our architecture includes a cache architecture using the locality of speech recognition, beam pruning using a dynamic threshold, two-stage language model searching, a parallel Gaussian Mixture Model (GMM) architecture based on the mixture level and frame level, a parallel Viterbi architecture, and pipeline operation between Viterbi transition and GMM processing. Results show that our architecture achieves 88.24% required frequency reduction (66.74MHz) and 84.04% memory bandwidth reduction (549.91MB/s) for real-time 60-k word continuous speech recognition.
- 2011-04-01
著者
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Noguchi Hiroki
Kobe University
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Yoshimoto Masahiko
Mitsubishi Electric Corporation
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Kawaguchi Hiroshi
Kobe Univ. Kobe‐shi Jpn
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YOSHIMOTO Masahiko
Kobe University
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MORITA Yasuhiro
Kobe University
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Kawaguchi Hiroshi
Department Of Computer Science And Systems Engineering Kobe University
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Yoshimoto Masahiko
System Lsi Development Center Mitsubishi Electric Corporation
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Yoshimoto M
Department Of Computer Science And Systems Engineering Kobe University
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MIURA Kazuo
Kobe University
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FUJINAGA Tsuyoshi
Kobe University
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SUGAHARA Takanobu
Kobe University
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