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Parallel Optimization Method in Language Model for Mandarin Speech Recognition

Author: JinZuo
Tutor: SunJiaSong
School: Tsinghua University
Course: Information and Communication Engineering
Keywords: Speech recognition N- tone pinyin grammar model Parallel Optimization Throughput
CLC: TN912.34
Type: Master's thesis
Year: 2010
Downloads: 87
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The language model is an important part of the speech recognition system , with the increased complexity of handling voice and corpus volume becomes large , the position of the rear end of the identification system , as the language models in the system is indispensable . Select the appropriate language model , and can greatly improve system performance , handling more natural speech recognition results closer to the speaker wants to express the true meaning . With our research , we found that in addition to the above indicators , the speech recognition system as a dialogue system that should provide to the user a friendly interface , higher recognition speed available to users . Therefore, the demand for the throughput of the system is gradually revealed. At the same time , the multi-core technology has been the rise of technology and parallel , which allows us to see the new space to improve system performance . Make good use of parallel technology , its application to the appropriate place of the system can exponentially enhance system performance . In this context , we use these technologies to optimize the language model of the existing Chinese tone recognition system , a new data model Trigram model quickly find and cache optimization based on the N- language model . New improvements proposed method can improve the throughput of nearly 3 times , preferably improve the performance of the system . In addition, in order to adapt to configure lower environmental configuration , we also proposed to optimize the language model in the calculation of high memory and CPU dependent , such as built-in functions , using the look-up table method to optimize the program consumes height calculations ( such as log calculation) , the removal of redundant computation program . These methods also improve the performance of the system can be small amplitude . After that , we use the parallel optimization techniques language model in the forward-backward algorithm parallel , so that the data in a shorter time can be adequately addressed improve the human-computer interaction , the waiting time and improve the real-time rate . The paper describes the principle of the different lengths of the parallel systems of a candidate sequence , and gives the realization . Finally, the experimental results on the 120 voice when 644.3 seconds long test data : real - time only 0.2375 , retrieval speed has been greatly improved . Speedup of 3.3 or more , indicating the superiority of the system .

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Electro-acoustic technology and speech signal processing > Speech Signal Processing > Speech Recognition and equipment
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