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Speech recognition Coding

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Shubham
Shubham 2011-2-4
编辑： Walter Roberson 2024-1-26
somebody please tell me how do i go about speech recognition coding.
  4 个评论
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SUHAS
SUHAS 2022-11-11
移动：DGM 2022-11-12
i need the matlab coding for speech recogniton

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回答（7 个）

Raviteja
Raviteja 2011-2-4
First you need fundamentals of speech processing. Witch includes speech signal basic sounds and features. DSP techniques like, FFT, Windowing,STFT.
Some basic signal processing tasks like finding energy, spectrum of speech, autocorrelation, zero crossing detection, silence speech removal techniques etc. Then feature extraction from speech signals.
Feature extraction (LPC,MFCC). Then classification process of feature vectros by VQ.
Then statistical modelling like HMM, GMM.
You need to go following books "Digital processing of speech signals" by Rabinar "Fundamentals of speech recognition" by Rabinar And good books for DSP.
Mostly you read IEEE papers.
Michelle Hirsch
Michelle Hirsch 2011-2-4
Is your goal to have speech recognition running in MATLAB, or to actually learn how to implement the algorithm?
If you just want to be able to use speech recognition in MATLAB, and you are running on Windows, you can pretty easily just incorporate the existing Windows capabilities using the MATLAB interface to .NET.
Here's some code my friend Jiro happened to pass around just the other day for this exact task. (Paste into a file in the editor and save).
function rec = speechrecognition
% Add assembly
NET.addAssembly('System.Speech');
% Construct engine
rec = System.Speech.Recognition.SpeechRecognitionEngine;
rec.SetInputToDefaultAudioDevice;
rec.LoadGrammar(System.Speech.Recognition.DictationGrammar);
% Define listener callback
addlistener(rec, 'SpeechRecognized', @recognizedFcn);
% Start recognition
rec.RecognizeAsync(System.Speech.Recognition.RecognizeMode.Multiple);
% Callback
function recognizedFcn(obj, e)
% Get text
txt = char(e.Result.Text);
% Split into words
w = regexp(txt, '\s', 'split');
if length(w) > 1
% Look for the occurrence of the phrase "search for"
idx = find(strcmp(w(1:end-1), 'search') & ...
strcmp(w(2:end), 'for'), 1, 'first');
if ~isempty(idx) && length(w) >= idx+2
% The words after are the search terms
searchTerm = sprintf('%s+', w{idx+2:end});
searchTerm(end) = '';
% Search on the web
web(['http://www.google.com/search?q=', searchTerm]);
fprintf(2, 'search for "%s"\n', strrep(searchTerm, '+', ' '));
else
%disp(txt)
end
elseif length(w) == 1 && strcmpi(w{1}, 'stop')
obj.RecognizeAsyncStop;
obj.delete;
%disp(txt);
disp('Stopping Speech Recognition. Thank you for using!');
else
%disp(txt);
end
  3 个评论
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Frandy
Frandy 2012-4-15
Hello I'm working on a project that involves using speech recognition. Now I tried to use your code but I am not sure on the actual process in which to have the code actually work. Do you mind explain?
Steven Dakin
Steven Dakin 2021-1-10
Some operational example code that uses this approach would be vey useful!

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Nada Gamal
Nada Gamal 2011-4-20
Hi Raviteja , I made all steps of speech recognition except of classification because i used Elcudien Distance and calculate the minium distance to the templates .And i have a problem now in how can i implement Hidden Markove model in speech recognition . i don't understand this algrothim . Thanks a lot :) Best Regards, Nada Gamal
veni
veni 2016-8-24
how to write the speech recognisation in matlab coding? how to record the speech in matlab?
Neha Tonpe
Neha Tonpe 2022-11-25
编辑：Walter Roberson 2022-11-25
function rec = speechrecognition
% Add assembly
NET.addAssembly('System.Speech');
% Construct engine
rec = System.Speech.Recognition.SpeechRecognitionEngine;
rec.SetInputToDefaultAudioDevice;
rec.LoadGrammar(System.Speech.Recognition.DictationGrammar);
% Define listener callback
addlistener(rec, 'SpeechRecognized', @recognizedFcn);
% Start recognition
rec.RecognizeAsync(System.Speech.Recognition.RecognizeMode.Multiple);
% Callback
function recognizedFcn(obj, e)
% Get text
txt = char(e.Result.Text);
% Split into words
w = regexp(txt, '\s', 'split');
if length(w) > 1
% Look for the occurrence of the phrase "search for"
idx = find(strcmp(w(1:end-1), 'search') & ...
strcmp(w(2:end), 'for'), 1, 'first');
if ~isempty(idx) && length(w) >= idx+2
% The words after are the search terms
searchTerm = sprintf('%s+', w{idx+2:end});
searchTerm(end) = '';
% Search on the web
web(['http://www.google.com/search?q=', searchTerm]);
fprintf(2, 'search for "%s"\n', strrep(searchTerm, '+', ' '));
else
%disp(txt)
end
elseif length(w) == 1 && strcmpi(w{1}, 'stop')
obj.RecognizeAsyncStop;
obj.delete;
%disp(txt);
disp('Stopping Speech Recognition. Thank you for using!');
else
%disp(txt);
end
Lavuri
Lavuri 2022-12-26
function rec = speechrecognition
% Add assembly
NET.addAssembly('System.Speech');
% Construct engine
rec = System.Speech.Recognition.SpeechRecognitionEngine;
rec.SetInputToDefaultAudioDevice;
rec.LoadGrammar(System.Speech.Recognition.DictationGrammar);
% Define listener callback
addlistener(rec, 'SpeechRecognized', @recognizedFcn);
% Start recognition
rec.RecognizeAsync(System.Speech.Recognition.RecognizeMode.Multiple);
% Callback
function recognizedFcn(obj, e)
% Get text
txt = char(e.Result.Text);
% Split into words
w = regexp(txt, '\s', 'split');
if length(w) > 1
% Look for the occurrence of the phrase "search for"
idx = find(strcmp(w(1:end-1), 'search') & ...
strcmp(w(2:end), 'for'), 1, 'first');
if ~isempty(idx) && length(w) >= idx+2
% The words after are the search terms
searchTerm = sprintf('%s+', w{idx+2:end});
searchTerm(end) = '';
% Search on the web
web(['http://www.google.com/search?q=', searchTerm]);
fprintf(2, 'search for "%s"\n', strrep(searchTerm, '+', ' '));
else
%disp(txt)
end
elseif length(w) == 1 && strcmpi(w{1}, 'stop')
obj.RecognizeAsyncStop;
obj.delete;
%disp(txt);
disp('Stopping Speech Recognition. Thank you for using!');
else
%disp(txt);
end
pathakunta
pathakunta 2024-1-26
First you need fundamentals of speech processing. Witch includes speech signal basic sounds and features. DSP techniques like, FFT, Windowing,STFT. Some basic signal processing tasks like finding energy, spectrum of speech, autocorrelation, zero crossing detection, silence speech removal techniques etc. Then feature extraction from speech signals. Feature extraction (LPC,MFCC). Then classification process of feature vectros by VQ. Then statistical modelling like HMM, GMM. You need to go following books "Digital processing of speech signals" by Rabinar "Fundamentals of speech recognition" by Rabinar And good books for DSP. Mostly you read IEEE papers.

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