毕业设计（论文）-利用HMM技术实现基于文本相关的语音识别设计.doc

内蒙古科技大学
本科生毕业设计说明书(毕业论文)
题目:利用HMM技术实现基于文本相关的语音识别
学生姓名:
学号:
专业:电子信息工程
班级:信息2003-4班
指导教师:
摘要
语音识别作为一个交叉学科,具有深远的研究价值。语音识别和语音合成技术已经成为现代技术发展的一个标志,也是现代计算机技术研究和发展的一个重要领域。虽然语音识别技术已经取得了一些成就,也有部分产品面世,但是,大多数语音识别系统仍局限于实验室,远没有达到实用化要求。制约实用化的根本原因可以归为两类,识别精度和系统复杂度。
HMM是一种用参数表示的用于描述随机过程统计特性的概率模型,它是由马尔可夫链演变来的,所以它是基于参数模型的统计识别方法。它是一个双重随机过程——具有一定状态数的隐马尔可夫链和显示随机函数集,每个函数都与链中一个状态相关联。“隐”的过程通过显示过程所产生的观察符号序列来表示,这就是隐马尔可夫模型。
本文主要介绍了语音识别的预处理,隐马尔可夫模型(Hidden Markov Models,HMM)和语音识别的基础理论和发展方向。对数字0~9的识别进行了详细的Matlab语言实现。
关键词:HMM;文本相关;语音识别
Abstract
As an interdisciplinary field, speech recognition is theoretically very valued .Speech recognition has e one of the important research fields and a mark of the development of science. Although speech technology has got some achievements, most speech recognition systems are still limited in lab and would have problems if migrated from lab which are much far from practicality. The ultimate reasons for restricting practicality can be classified to two kinds, one is precision for recognition and the other plexity of the system.
HMM is one kind expresses with the parameter uses in the description stochastic process statistical property probabilistic model, it is may the husband chain evolve by Mar, therefore it based on parameter model statistics recognition method. It is a dual stochastic process – has the certain condition number to hide type Markov to be possible the husband chain and the demonstration stochastic function collection, each function all a condition is connected with the chain in. Hidden Markov process the observation mark sequence which produces through the demonstration process to indicate that, this is hides type Markov to be possible the husband model.
This article mainly introduced the speech recognition pretreatment, hides Mar to be possible the husband model (Hidden Markov Models, HMM) and the speech recognition basic theory and the development direction. Has carried on the detailed Matlab language realization to the num