The Dynamically-Adjustable Histogram Pruning Method for Embedded Voice Dialing

D. Chen, F. Zheng, J. Liu, J. Deng, W. Wu, Z. Song, and X. Zhou (PRC)


Speech Recognition, Voice Dialing, User definable Vocabulary, Dynamically-Adjustable Histogram Pruning


Memory and speed are two key factors that must be faced when applying voice dialer to Pocket PCs. To provide a solution, a novel decoding method integrated with the score differences of token paths is proposed, named as “Dynamically-Adjustable Histogram Pruning”. Additionally, the computation of likelihood score is accelerated by means of dynamic score lookup table. Furthermore, a new acoustic modeling method based on Extended Initial/Final (XIF) with less dimensioned acoustic feature is proven suitable for embedded speech command recognition. By adopting the methods developed above, we implement a speaker-independent, user definable voice dialing speech recognition system with good performance on a real PDA device. For a 200-Chinese-word vocabulary, its recognition accuracy reaches 97.80%. Meanwhile, it obtains better recognition speed by 80 times and saves decoding space by 30% in comparison to the baseline system using standard Viterbi decoding method.

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