matlab語音識(shí)別系統(tǒng)(源代碼)最新版-(共18頁)

1、目錄一、 設(shè)計(jì)任務(wù)及要求1二、 語音識(shí)別的簡單介紹2.1語者識(shí)別的概念2 2.2特征參數(shù)的提取3 2.3用矢量量化聚類法生成碼本3 2.4VQ的說話人識(shí)別 4三、 算法程序分析3.1函數(shù)關(guān)系.4 3.2代碼說明5 3.2.1函數(shù)mfcc5 3.2.2函數(shù)disteu5 3.2.3函數(shù)vqlbg.63.2.4函數(shù)test63.2.5函數(shù)testDB7 3.2.6 函數(shù)train8 3.2.7函數(shù)melfb8四、 演示分析.9五、 心得體會(huì).11附：GUI程序代碼12一、 設(shè)計(jì)任務(wù)及要求用MATLAB實(shí)現(xiàn)簡單的語音識(shí)別功能；具體設(shè)計(jì)要求如下： 用MATLAB實(shí)現(xiàn)簡單的數(shù)字19的語音識(shí)別功能。二、

2、語音識(shí)別的簡單介紹基于VQ的說話人識(shí)別系統(tǒng)，矢量量化起著雙重作用。在訓(xùn)練階段，把每一個(gè)說話者所提取的特征參數(shù)進(jìn)行分類，產(chǎn)生不同碼字所組成的碼本。在識(shí)別(匹配)階段，我們用VQ方法計(jì)算平均失真測度(本系統(tǒng)在計(jì)算距離d時(shí)，采用歐氏距離測度)，從而判斷說話人是誰。語音識(shí)別系統(tǒng)結(jié)構(gòu)框圖如圖1所示。圖1 語音識(shí)別系統(tǒng)結(jié)構(gòu)框圖2.1語者識(shí)別的概念語者識(shí)別就是根據(jù)說話人的語音信號(hào)來判別說話人的身份。語音是人的自然屬性之一，由于說話人發(fā)音器官的生理差異以及后天形成的行為差異，每個(gè)人的語音都帶有強(qiáng)烈的個(gè)人色彩，這就使得通過分析語音信號(hào)來識(shí)別說話人成為可能。用語音來鑒別說話人的身份有著許多獨(dú)特的優(yōu)點(diǎn)，如語音是人的

3、固有的特征，不會(huì)丟失或遺忘；語音信號(hào)的采集方便，系統(tǒng)設(shè)備成本低；利用電話網(wǎng)絡(luò)還可實(shí)現(xiàn)遠(yuǎn)程客戶服務(wù)等。因此，近幾年來，說話人識(shí)別越來越多的受到人們的重視。與其他生物識(shí)別技術(shù)如指紋識(shí)別、手形識(shí)別等相比較，說話人識(shí)別不僅使用方便，而且屬于非接觸性，容易被用戶接受，并且在已有的各種生物特征識(shí)別技術(shù)中，是唯一可以用作遠(yuǎn)程驗(yàn)證的識(shí)別技術(shù)。因此，說話人識(shí)別的應(yīng)用前景非常廣泛：今天，說話人識(shí)別技術(shù)已經(jīng)關(guān)系到多學(xué)科的研究領(lǐng)域，不同領(lǐng)域中的進(jìn)步都對(duì)說話人識(shí)別的發(fā)展做出了貢獻(xiàn)。說話人識(shí)別技術(shù)是集聲學(xué)、語言學(xué)、計(jì)算機(jī)、信息處理和人工智能等諸多領(lǐng)域的一項(xiàng)綜合技術(shù)，應(yīng)用需求將十分廣闊。在吃力語音信號(hào)的時(shí)候如何提取信號(hào)中關(guān)

4、鍵的成分尤為重要。語音信號(hào)的特征參數(shù)的好壞直接導(dǎo)致了辨別的準(zhǔn)確性。2.2特征參數(shù)的提取對(duì)于特征參數(shù)的選取，我們使用mfcc的方法來提取。MFCC參數(shù)是基于人的聽覺特性利用人聽覺的屏蔽效應(yīng)，在Mel標(biāo)度頻率域提取出來的倒譜特征參數(shù)。 MFCC參數(shù)的提取過程如下： 1. 對(duì)輸入的語音信號(hào)進(jìn)行分幀、加窗，然后作離散傅立葉變換，獲得頻譜分布信息。 設(shè)語音信號(hào)的DFT為：（1）其中式中x(n)為輸入的語音信號(hào)，N表示傅立葉變換的點(diǎn)數(shù)。 2. 再求頻譜幅度的平方，得到能量譜。 3. 將能量譜通過一組Mel尺度的三角形濾波器組。 我們定義一個(gè)有M個(gè)濾波器的濾波器組（濾波器的個(gè)數(shù)和臨界帶的個(gè)數(shù)相近），采用的濾

5、波器為三角濾波器，中心頻率為f(m),m=1,2,3,，M本系統(tǒng)取M=100。4. 計(jì)算每個(gè)濾波器組輸出的對(duì)數(shù)能量。 （2）其中為三角濾波器的頻率響應(yīng)。 5. 經(jīng)過離散弦變換（DCT）得到MFCC系數(shù)。 MFCC系數(shù)個(gè)數(shù)通常取2030，常常不用0階倒譜系數(shù)，因?yàn)樗从车氖穷l譜能量，故在一般識(shí)別系統(tǒng)中，將稱為能量系數(shù)，并不作為倒譜系數(shù)，本系統(tǒng)選取20階倒譜系數(shù)。2.3用矢量量化聚類法生成碼本 我們將每個(gè)待識(shí)的說話人看作是一個(gè)信源，用一個(gè)碼本來表征。碼本是從該說話人的訓(xùn)練序列中提取的MFCC特征矢量聚類而生成。只要訓(xùn)練的序列足夠長，可認(rèn)為這個(gè)碼本有效地包含了說話人的個(gè)人特征，而與講話的內(nèi)容無關(guān)。

6、本系統(tǒng)采用基于分裂的LBG的算法設(shè)計(jì)VQ碼本，為訓(xùn)練序列，B為碼本。 具體實(shí)現(xiàn)過程如下： 1. 取提取出來的所有幀的特征矢量的型心(均值)作為第一個(gè)碼字矢量B1。2. 將當(dāng)前的碼本Bm根據(jù)以下規(guī)則分裂，形成2m個(gè)碼字。 （4）其中m從1變化到當(dāng)前的碼本的碼字?jǐn)?shù)，是分裂時(shí)的參數(shù)，本文=0.01。 3. 根據(jù)得到的碼本把所有的訓(xùn)練序列(特征矢量)進(jìn)行分類，然后按照下面兩個(gè)公式計(jì)算訓(xùn)練矢量量化失真量的總和以及相對(duì)失真(n為迭代次數(shù)，初始n=0，=，B為當(dāng)前的碼書)，若相對(duì)失真小于某一閾值，迭代結(jié)束，當(dāng)前的碼書就是設(shè)計(jì)好的2m個(gè)碼字的碼書，轉(zhuǎn)。否則，轉(zhuǎn)下一步。 量化失真量和： （5）相對(duì)失真： （6）

7、 4. 重新計(jì)算各個(gè)區(qū)域的新型心，得到新的碼書，轉(zhuǎn)3。 5. 重復(fù) ， 和步，直到形成有M個(gè)碼字的碼書(M是所要求的碼字?jǐn)?shù))，其中D0=10000。 2.4 VQ的說話人識(shí)別 設(shè)是未知的說話人的特征矢量，共有T幀是訓(xùn)練階段形成的碼書，表示碼書第m個(gè)碼字，每一個(gè)碼書有M個(gè)碼字。再計(jì)算測試者的平均量化失真D，并設(shè)置一個(gè)閾值，若D小于此閾值，則是原訓(xùn)練者，反之則認(rèn)為不是原訓(xùn)練者。 （7）三、 算法程序分析在具體的實(shí)現(xiàn)過程當(dāng)中，采用了matlab軟件來幫助完成這個(gè)項(xiàng)目。在matlab中主要由采集，分析，特征提取，比對(duì)幾個(gè)重要部分。以下為在實(shí)際的操作中，具體用到得函數(shù)關(guān)系和作用一一列舉在下面。3.1函數(shù)

8、關(guān)系主要有兩類函數(shù)文件Train.m和Test.m在Train.m調(diào)用Vqlbg.m獲取訓(xùn)練錄音的vq碼本，而，接著mfcc.m調(diào)用Melfb.m-將能量譜通過一組Mel尺度的三角形濾波器組。 在Test.m函數(shù)文件中調(diào)用Disteu.m計(jì)算訓(xùn)練錄音（提供vq碼本）與測試錄音（提供mfcc）mel倒譜系數(shù)的距離，即判斷兩聲音是否為同一錄音者提供。mfcc.m調(diào)用Melfb.m-將能量譜通過一組Mel尺度的三角形濾波器組。 3.2具體代碼說明3.2.1函數(shù)mffc:function r = mfcc(s, fs)-m = 100;n = 256;l = length(s);nbFrame = f

9、loor(l - n) / m) + 1; %沿-方向取整 for i = 1:nfor j = 1:nbFrameM(i, j) = s(j - 1) * m) + i); %對(duì)矩陣M賦值endendh = hamming(n); %加 hamming 窗，以增加音框左端和右端的連續(xù)性M2 = diag(h) * M;for i = 1:nbFrameframe(:,i) = fft(M2(:, i); %對(duì)信號(hào)進(jìn)行快速傅里葉變換FFT endt = n / 2;tmax = l / fs;m = melfb(20, n, fs); %將上述線性頻譜通過Mel 頻率濾波器組得到Mel 頻譜,

10、下面在將其轉(zhuǎn)化成對(duì)數(shù)頻譜n2 = 1 + floor(n / 2);z = m * abs(frame(1:n2, :).2;r = dct(log(z); %將上述對(duì)數(shù)頻譜，經(jīng)過離散余弦變換(DCT)變換到倒譜域，即可得到Mel 倒譜系數(shù)(MFCC參數(shù))3.2.2函數(shù)disteu-計(jì)算測試者和模板碼本的距離function d = disteu(x, y)M, N = size(x); %音頻x賦值給【M，N】M2, P = size(y); %音頻y賦值給【M2，P】if (M = M2) error(不匹配！) %兩個(gè)音頻時(shí)間長度不相等endd = zeros(N, P);if (N P

11、)%在兩個(gè)音頻時(shí)間長度相等的前提下 copies = zeros(1,P); for n = 1:N d(n,:) = sum(x(:, n+copies) - y) .2, 1); endelse copies = zeros(1,N); for p = 1:P d(:,p) = sum(x - y(:, p+copies) .2, 1); end%成對(duì)歐氏距離的兩個(gè)矩陣的列之間的距離endd = d.0.5;3.2.3函數(shù)vqlbg-該函數(shù)利用矢量量化提取了音頻的vq碼本function r = vqlbg(d,k)e = .01;r = mean(d, 2);dpr = 10000;fo

12、r i = 1:log2(k) r = r*(1+e), r*(1-e); while (1 = 1) z = disteu(d, r); m,ind = min(z, , 2); t = 0; for j = 1:2i r(:, j) = mean(d(:, find(ind = j), 2); x = disteu(d(:, find(ind = j), r(:, j); for q = 1:length(x) t = t + x(q); end end if (dpr - t)/t) e) break; else dpr = t; end endend3.2.4函數(shù)testfunctio

13、n finalmsg = test(testdir, n, code)for k = 1:n % read test sound file of each speaker file = sprintf(%ss%d.wav, testdir, k); s, fs = wavread(file); v = mfcc(s, fs); % 得到測試人語音的mel倒譜系數(shù)distmin = 4; %閾值設(shè)置處 % 就判斷一次，因?yàn)槟０謇锩嬷挥幸粋€(gè)文件 d = disteu(v, code1); %計(jì)算得到模板和要判斷的聲音之間的“距離” dist = sum(min(d,2) / size(d,1);

14、%變換得到一個(gè)距離的量 %測試閾值數(shù)量級(jí) msgc = sprintf(與模板語音信號(hào)的差值為:%10f , dist); disp(msgc); %此人匹配 if dist distmin msg = sprintf(第%d位說話者與模板語音信號(hào)不匹配,不符合要求!n, k); finalmsg = 此位說話者不符合要求!; %界面顯示語句，可隨意設(shè)定 disp(msg); end end3.2.5函數(shù)testDB這個(gè)函數(shù)實(shí)際上是對(duì)數(shù)據(jù)庫一個(gè)查詢,根據(jù)測試者的聲音,找相應(yīng)的文件,并且給出是誰的提示function testmsg = testDB(testdir, n, code)nameL

15、ist=1,2,3,4,5,6,7,8,9 ; %這個(gè)是我們要識(shí)別的9個(gè)數(shù)for k = 1:n % 數(shù)據(jù)庫中每一個(gè)說話人的特征 file = sprintf(%ss%d.wav, testdir, k);%找出文件的路徑 s, fs = wavread(file); v = mfcc(s, fs); % 對(duì)找到的文件取mfcc變換 distmin = inf; k1 = 0; for l = 1:length(code) d = disteu(v, codel); dist = sum(min(d,2) / size(d,1); if dist distmin distmin = dist;

16、%這里和test函數(shù)里面一樣 但多了一個(gè)具體語者的識(shí)別 k1 = l; end end msg=nameListk1 msgbox(msg);end3.2.6 函數(shù)train-該函數(shù)就是對(duì)音頻進(jìn)行訓(xùn)練，也就是提取特征參數(shù)function code = train(traindir, n)k = 16; % number of centroids requiredfor i = 1:n % 對(duì)數(shù)據(jù)庫中的代碼形成碼本 file = sprintf(%ss%d.wav, traindir, i); disp(file); s, fs = wavread(file); v = mfcc(s, fs);

17、 % 計(jì)算 MFCCs 提取特征特征，返回值是Mel倒譜系數(shù)，是一個(gè)log的dct得到的 codei = vqlbg(v, k); % 訓(xùn)練VQ碼本 通過矢量量化，得到原說話人的VQ碼本end3.2.7 函數(shù)melfb-確定矩陣的濾波器function m = melfb(p, n, fs)f0 = 700 / fs;fn2 = floor(n/2);lr = log(1 + 0.5/f0) / (p+1);% convert to fft bin numbers with 0 for DC termbl = n * (f0 * (exp(0 1 p p+1 * lr) - 1);直接轉(zhuǎn)換為F

18、FT的數(shù)字模型b1 = floor(bl(1) + 1;b2 = ceil(bl(2);b3 = floor(bl(3);b4 = min(fn2, ceil(bl(4) - 1;pf = log(1 + (b1:b4)/n/f0) / lr;fp = floor(pf);pm = pf - fp;r = fp(b2:b4) 1+fp(1:b3);c = b2:b4 1:b3 + 1;v = 2 * 1-pm(b2:b4) pm(1:b3);m = sparse(r, c, v, p, 1+fn2)；四、 演示分析我們的功能分為兩部分:對(duì)已經(jīng)保存的9個(gè)數(shù)字的語音進(jìn)行辨別和實(shí)時(shí)的判斷說話人說的是

19、否為一個(gè)數(shù).在前者的實(shí)驗(yàn)過程中,先把9個(gè)數(shù)字的聲音保存成wav的格式,放在一個(gè)文件夾中,作為一個(gè)檢測的數(shù)據(jù)庫.然后對(duì)檢測者實(shí)行識(shí)別,系統(tǒng)給出提示是哪個(gè)數(shù)字.在第二個(gè)功能中,實(shí)時(shí)的錄取一段說話人的聲音作為模板,提取mfcc特征參數(shù),隨后緊接著進(jìn)行遇著識(shí)別,也就是讓其他人再說相同的話,看是否是原說話者.實(shí)驗(yàn)過程及具體功能如下：先打開Matlab 使Current Directory為錄音及程序所所在的文件夾再打開文件“enter.m”，點(diǎn)run運(yùn)行，打開enter界面，點(diǎn)擊“進(jìn)入”按鈕進(jìn)入系統(tǒng)。（注：文件包未封裝完畢，目前只能通過此方式打開運(yùn)行。）（如下圖figure1） figure1在對(duì)數(shù)據(jù)庫

20、中已有的語者進(jìn)行識(shí)別模塊:選擇載入語音庫語音個(gè)數(shù)；點(diǎn)擊語音庫錄制模版進(jìn)行已存語音信息的提取；點(diǎn)擊錄音-test進(jìn)行現(xiàn)場錄音；點(diǎn)擊語者判斷進(jìn)行判斷數(shù)字，并顯示出來。在實(shí)時(shí)語者識(shí)別模塊:點(diǎn)擊實(shí)時(shí)錄制模板上的“錄音-train”按鈕,是把新語者的聲音以wav格式存放在”實(shí)時(shí)模板”文件夾中, 接著點(diǎn)擊“實(shí)時(shí)錄制模板”，把新的模板提取特征值。隨后點(diǎn)擊實(shí)時(shí)語者識(shí)別模板上的“錄音-train”按鈕,是把語者的聲音以wav格式存放在”測試”文件夾中,再點(diǎn)擊“實(shí)時(shí)語者識(shí)別”，在對(duì)測得的聲音提取特征值的同時(shí)，和實(shí)時(shí)模板進(jìn)行比對(duì)，然后得出是否是實(shí)時(shí)模板中的語者。另外面板上的播放按鈕都是播放相對(duì)應(yīng)左邊錄取的聲音。想要

21、測量多次，只要接著錄音，自動(dòng)保存，然后程序比對(duì)音頻就可以。退出只要點(diǎn)擊菜單File/Exit，退出程序。程序運(yùn)行截圖：（fig.2）運(yùn)行后系統(tǒng)界面五、 心得體會(huì)實(shí)驗(yàn)表明，該系統(tǒng)能較好地進(jìn)行語音的識(shí)別，同時(shí)，基于矢量量化技術(shù) （）的語音識(shí)別系統(tǒng)具有分類準(zhǔn)確，存儲(chǔ)數(shù)據(jù)少，實(shí)時(shí)響應(yīng)速度快等綜合性能好的特點(diǎn)矢量量化技術(shù)在語音識(shí)別的應(yīng)用方面，尤其是在孤立詞語音識(shí)別系統(tǒng)中得到很好的應(yīng)用，特別是有限狀態(tài)矢量量化技術(shù)，對(duì)于語音識(shí)別更為有效。通過這次課程設(shè)計(jì)，我對(duì)語音識(shí)別有了更加形象化的認(rèn)識(shí)，也強(qiáng)化了MATLAB的應(yīng)用，對(duì)將來的學(xué)習(xí)奠定了基礎(chǔ)。附：GUI程序代碼function varargout = unti

22、tled2(varargin)% UNTITLED2 M-file for untitled2.fig% UNTITLED2, by itself, creates a new UNTITLED2 or raises the existing% singleton*.% H = UNTITLED2 returns the handle to a new UNTITLED2 or the handle to% the existing singleton*.% UNTITLED2(CALLBACK,hObject,eventData,handles,.) calls the local% fun

23、ction named CALLBACK in UNTITLED2.M with the given input arguments.% UNTITLED2(Property,Value,.) creates a new UNTITLED2 or raises the% existing singleton*. Starting from the left, property value pairs are% applied to the GUI before untitled2_OpeningFunction gets called. An% unrecognized property na

24、me or invalid value makes property application% stop. All inputs are passed to untitled2_OpeningFcn via varargin.% *See GUI Options on GUIDEs Tools menu. Choose GUI allows only one% instance to run (singleton).% See also: GUIDE, GUIDATA, GUIHANDLES % Copyright 2002-2003 The MathWorks, Inc. % Edit th

25、e above text to modify the response to help untitled2 % Last Modified by GUIDE v2.5 08-Jun-2010 23:58:57% Begin initialization code - DO NOT EDITgui_Singleton = 1;gui_State = struct(gui_Name, mfilename, . gui_Singleton, gui_Singleton, . gui_OpeningFcn, untitled2_OpeningFcn, . gui_OutputFcn, untitled

26、2_OutputFcn, . gui_LayoutFcn, , . gui_Callback, );if nargin & ischar(varargin1) gui_State.gui_Callback = str2func(varargin1);endif nargout varargout1:nargout = gui_mainfcn(gui_State, varargin:);else gui_mainfcn(gui_State, varargin:);end% End initialization code - DO NOT EDIT% - Executes just before

27、untitled2 is made visible.function untitled2_OpeningFcn(hObject, eventdata, handles, varargin)% This function has no output args, see OutputFcn.% hObject handle to figure% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% va

28、rargin command line arguments to untitled2 (see VARARGIN)% Choose default command line output for untitled2handles.output = hObject;% Update handles structureguidata(hObject, handles);axes(findobj(tag,axes13);imshow(3.jpg);axes(findobj(tag,axes12);imshow(1.jpg);% UIWAIT makes untitled2 wait for user

29、 response (see UIRESUME)% uiwait(handles.figure1);% - Outputs from this function are returned to the command line.function varargout = untitled2_OutputFcn(hObject, eventdata, handles) % varargout cell array for returning output args (see VARARGOUT);% hObject handle to figure% eventdata reserved - to

30、 be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Get default command line output from handles structurevarargout1 = handles.output;% - Executes on button press in pushbutton1.function pushbutton1_Callback(hObject, eventdata, handles)% hObject han

31、dle to pushbutton1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)Channel_Str=get(handles.popupmenu3,String); Channel_Number=str2double(Channel_Strget(handles.popupmenu3,Value); global moodle;moodle = train(模版,C

32、hannel_Number) % - Executes on button press in pushbutton2.function pushbutton2_Callback(hObject, eventdata, handles)% hObject handle to pushbutton2 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handglobal data1;global moodle ;test(測試,1,moodle)% % -function Open_Callb

33、ack(hObject, eventdata, handles)% hObject handle to Open (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)filename,pathname=uigetfile()file=get(handles.edits,filename,pathname)y,f,b=wavread(file);% -function Exit_

34、Callback(hObject, eventdata, handles)% hObject handle to Exit (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)exit% -function About_Callback(hObject, eventdata, handles)% hObject handle to About (see GCBO)% event

35、data reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)H=語者識(shí)別helpdlg(H,help text)% -function File_Callback(hObject, eventdata, handles)% hObject handle to File (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB

36、% handles structure with handles and user data (see GUIDATA)% -function Edit_Callback(hObject, eventdata, handles)% hObject handle to Edit (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% -function Help_Callback

37、(hObject, eventdata, handles)% hObject handle to Help (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% - Executes on button press in pushbutton7.function pushbutton7_Callback(hObject, eventdata, handles)% hObjec

38、t handle to pushbutton7 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)msg=請(qǐng)速度錄音msgbox(msg)clearglobal data1;%global dataDN1;AI = analoginput(winsound);chan = addchannel(AI,1:2);duration = 3; %1 second acquisiti

39、onset(AI,SampleRate,8000)ActualRate = get(AI,SampleRate);set(AI,SamplesPerTrigger,duration*ActualRate)set(AI,TriggerType,Manual)blocksize = get(AI,SamplesPerTrigger);Fs = ActualRate;start(AI)trigger(AI)data1,time,abstime,events = getdata(AI);fname=sprintf(E:Matlab語音識(shí)別系統(tǒng)實(shí)時(shí)模版s1.wav)%dataDN1=wden(data1

40、,heursure,s,one,5,sym8);denoisewavwrite(data1,fname)msgbox(fname)% - Executes on button press in pushbutton8.function pushbutton8_Callback(hObject, eventdata, handles)% hObject handle to pushbutton8 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with

41、handles and user data (see GUIDATA)global data1;%global dataDN1;sound(data1)%sound(dataDN1)axes(handles.axes1)%set to plot at axes1 plot(data1);%plot(dataDN1);xlabel(訓(xùn)練采樣序列),ylabel(信號(hào)幅);%xlabel(),ylabel(sym8);grid on;clear % - Executes on button press in pushbutton9.function pushbutton9_Callback(hOb

42、ject, eventdata, handles)% hObject handle to pushbutton9 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)msg=請(qǐng)速度錄音msgbox(msg)clearglobal data2;%global dataDN2;AI = analoginput(winsound);chan = addchannel(AI,1:2);

43、duration = 3; %1 second acquisitionset(AI,SampleRate,8000)ActualRate = get(AI,SampleRate);set(AI,SamplesPerTrigger,duration*ActualRate)set(AI,TriggerType,Manual)blocksize = get(AI,SamplesPerTrigger);Fs = ActualRate;start(AI)trigger(AI)data2,time,abstime,events = getdata(AI);fname=sprintf(E:Matlab語音識(shí)

44、別系統(tǒng)測試s1.wav)%dataDN1=wden(data1,heursure,s,one,5,sym8);denoisewavwrite(data2,fname)msgbox(fname)% - Executes on button press in pushbutton10.function pushbutton10_Callback(hObject, eventdata, handles)% hObject handle to pushbutton10 (see GCBO)% eventdata reserved - to be defined in a future version

45、of MATLAB% handles structure with handles and user data (see GUIDATA)global data2;%global dataDN2;sound(data2)%sound(dataDN2)axes(handles.axes2)%set to plot at axes1 plot(data2);%plot(dataDN2);xlabel(測試采樣序列),ylabel(信號(hào)幅);%xlabel(),ylabel(sym8);%grid on;clear % - Executes on button press in pushbutton

46、11.function pushbutton11_Callback(hObject, eventdata, handles)% hObject handle to pushbutton11 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)global moodle ;testDB(測試,1,moodle)% - Executes on button press in pus

47、hbutton12.function pushbutton12_Callback(hObject, eventdata, handles)% hObject handle to pushbutton12 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)global moodle;moodle = train(實(shí)時(shí)模板,1) % - Executes on selection

48、 change in popupmenu3.function popupmenu3_Callback(hObject, eventdata, handles)% hObject handle to popupmenu3 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Hints: contents = get(hObject,String) returns popupmenu3 contents as cell array% contentsget(hObject,Value)