汉语语音识别的平滑声韵基元HMM算法  

Smoothed-unit HMM Algorithm in Mandarin Speech Recognition

作　　者：何强[1] 毛士艺[1] 张有为[2] 

机构地区：[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

出　　处：《北京航空航天大学学报》2001年第2期146-149,共4页Journal of Beijing University of Aeronautics and Astronautics

基　　金：广东省自然科学基金资助项目!(96 0 6 31)

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 .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 is 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 is fit for real-time systems with DSP kernel.

关 键 词：语音识别 马尔柯夫过程 HMM 声韵基元 平滑声韵基元 算法 汉语语音 

分 类 号：TN912.3[电子电信—通信与信息系统]