【正文】 .................. 5 ...................................................................................... 5 ........................................................................... 6 ........................................................................... 7 ............................................................................................. 7 ...................................................................................... 7 ...................................................................................... 8 ......................................................................................... 8 .................................................................................. 9 .................................................................................. 9 .............................................................................. 11 ...........................................12 .................................................................................13 .................................................................................14 .....................................................................................14 ..............................................................................14 ............................................................................................15 LPCC倒譜系數(shù) ................................................................................15 Mel頻率倒譜系數(shù) ..........................................................................16 三、語音識別主要算法 ...........................................................................................17 .....................................................................................17 ..........................................................................18 .....................................................................................19 ........................................................................................20 HMM和 ANN的混合模型 ..............................................................................21 四、隱含馬爾可夫模型算法 ....................................................................................23 HMM的基本理論和數(shù)學描述 .......................................................................23 HMM的三個基本問題及解決算法 ................................................................24 HMM算法的改進 ........................................................................................31 河南理工大學畢業(yè)設計（論文）說明書 IV HMM的結構和類型 .....................................................................................33 HMM算法實現(xiàn)的問題 .................................................................................34 五、基于 Matlab環(huán)境下的語音識別算法實現(xiàn) ..........................................................35 .....................................................................................35 Matlab中 HMM算法的實現(xiàn) .....................................................................36 ........................................................................................36 .................................................................................36 .....................................................................................37 ............................................................................................38 六、結束語 .............................................................................................................39 回顧 ...........................................................................................................39 展望 ...........................................................................................................39 七、致謝 ................................................................................................................40 參考文獻 ................................................................................................................40 河南理工大學畢業(yè)設計（論文）說明書 1 一、 前言 語音識別的發(fā)展歷史 作為智能計算機研究的主導方向和人機語音通信的關鍵技術，語音識別技術一直受到各國科學界的廣泛關注。 Matlab 是一款功能強大的數(shù)學軟件，它附帶大量的信號處理工具箱為信號分析研究，特別是文中主要探討的聲波分析研究帶來極大便利。本文基于語音信號產(chǎn)生的數(shù)學模型，從時域、頻域出發(fā)對語音信號進行分析，論述了語音識別的基本理論。語音識別技術既是國際競爭的一項重要技術，也是每一個國家經(jīng)濟發(fā)展不可缺少的重要技術支撐。 語音識別算法有多種實現(xiàn)方案，本文采取的方法是利用 Matlab 強大的數(shù)學運算能力，實現(xiàn)孤立語音信號的識別。 關鍵詞 ：語音識別算法； HMM 模型； Matlab； GUI ABSTRACT Speech Recognition is designed to allow machines to understand what people say,and accurately identify the contents of voice to execute the intent of recognition technology is not only an important internationally peted technology,but also an indispensable foundational technology for the national economic on the mathematical model from the speech signal,this paper analyze audio signal from the time domain,frequency domain proceeding,and discussed the basic theory of speech recognition algorithm are discussed:Dynamic Time Warping(DTW)、 Rulebased Artificial Intelligence,Artificial Neural Network(ANN),Hidden Markov Model(HMM),HMM bined with focus is put in the theoretical studies of Hidden Markov(HMM) model algorithm,and the classical HMM algorithm is improved. Speech recognition algorithm is realized in various programs,this article taking the method is to use Matlab powerful mathematical operation ability to realize the recognition of speech signal isolation. Matlab is a powerful mathematic software with a mass of toolboxes dealing with signal processing. It gives a terrific shortcut to the research of signal processing,especially the wave analysis. We can characterize the sound with key parameters such as intensity, frequency etc. In this paper, hidden Markov model (HMM) recognition algorithm using MFCC (MEL 河南理工大學畢業(yè)設計（論文）說明書 II frequency cepstral coefficients) as the main voice characteristic parameters, the establishment of a Chinese digital speech recognition system, including the preprocessing of the speech signa