Speech recognition Coding
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somebody please tell me how do i go about speech recognition coding.
4 Commenti
Risposte (7)
Raviteja
il 4 Feb 2011
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.
0 Commenti
Michelle Hirsch
il 4 Feb 2011
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 Commenti
Frandy
il 15 Apr 2012
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
il 10 Gen 2021
Some operational example code that uses this approach would be vey useful!
Nada Gamal
il 20 Apr 2011
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
il 24 Ago 2016
how to write the speech recognisation in matlab coding? how to record the speech in matlab?
1 Commento
Walter Roberson
il 25 Ago 2016
See audiorecorder() to record the speech. http://www.mathworks.com/help/matlab/ref/audiorecorder.html
Neha Tonpe
il 25 Nov 2022
Modificato: Walter Roberson
il 25 Nov 2022
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
0 Commenti
Lavuri
il 26 Dic 2022
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
0 Commenti
pathakunta
il 26 Gen 2024
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.
0 Commenti
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