北京航空航天大学学报 ›› 2001, Vol. 27 ›› Issue (2): 146-149.

• 论文 • 上一篇    下一篇

汉语语音识别的平滑声韵基元HMM算法

何强1, 毛士艺1, 张有为2   

  1. 1. 北京航空航天大学 电子工程系;
    2. 五邑大学 信息科学研究所
  • 收稿日期:1999-11-12 出版日期:2001-02-28 发布日期:2010-09-27
  • 作者简介:何 强(1972-),男,天津人,博士生,100083,北京.
  • 基金资助:

    广东省自然科学基金资助项目(960631)

Smoothed-unit HMM Algorithm in Mandarin Speech Recognition

HE Qiang1, MAO Shi-yi1, ZHANG You-wei2   

  1. 1. Beijing University of Aeronautics and Astronautics, Dept. of Electronic Engineering;
    2. Wuyi University, Research Institute of Information Science
  • Received:1999-11-12 Online:2001-02-28 Published:2010-09-27

摘要: 汉语语音识别的基本单元一般为音素、音节以及声韵母.以声韵母为基元的识别系统由于HMM模型较少,计算量小,适合于实时实现.但是由于模型比较孤立,对语音信号的声学特性描述得不够精确,因而识别率一般比音节基元的系统低.而以音节、音素(tri-phone、di-phone)为基元的系统则有HMM模型数量多、训练和识别过程中计算量大的缺点,影响到系统的实时性.本文提出了一种折衷的方案,系统基元仍选择声韵母,而在HMM训练阶段,对整个音节序列的参数进行运算,使声韵过渡段的状态得到平滑,同时计算并保存每个音节声韵之间的转移概率,识别时动态组装为完整的音节HMM.该方法在保持少量HMM个数的同时,能够降低误试率,适合于以DSP为核心的实时连接词语音识别系统.

Abstract: The base unit in mandarin speech recognition is phoneme, semi-syllable or syllable. Semi-syllable system has fewer HMM models and needs less computation, thus it's suitable for real-time systems. But due to poor description for the acoustic properties of the speech signal, it generally shows a low performance compared with syllable system. While the system based on syllable or phoneme (tri-phone or di-phone) has much more HMM models, and needs massive computation in training and recognition, which goes against to real-time implementation. The new scheme is a compromised one. The new system is based on semi-syllable system, but the parameters of the entire syllable are used in training phase, so smoothing between two semi-syllable units is introduced. The transition probability between semi-syllables is calculated, and the two semi-syllable HMMs are connected into a full syllable HMM in recognition phase. This can increase the system performance without increasing HMM models, and it's fit for real-time systems with DSP kernel.

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