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Wavelet Subband coding for speaker recognition

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fn extracts wavelet feature vector which could be used for speaker recogniton from speech signal.

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Description

The fn will calculated subband energes as given in the att tech paper of ruhi sarikaya and others. the fn also calculates the DCT part. using this fn and other algo for pattern classification(VQ,GMM) speaker identification could be achived. the progress in extraction is also indicated by progress bar.

Acknowledgements

Status / Progress Indicator inspired this file.

Required Products Wavelet Toolbox
MATLAB release MATLAB 7 (R14)
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Comments and Ratings (7)
09 Apr 2014 Chameera Wijebadnara  
01 Mar 2013 Guillermo

dear raghu ram:

the sbc_2 function is asking me for a "en" function "energy(1)=en(coef(1:s_no(1)));" where can i get it?
thnx

01 Mar 2013 Guillermo

dear raghu ram:

the sbc_2 function is asking me for a "en" function "energy(1)=en(coef(1:s_no(1)));" where can i get it?
thnx

02 Feb 2013 ahmed alhamdani

Dear raghu ram ;

Thank you for interested.

Summry:

The specific for what I need help is about how I can use the output data from SVM as input to HMM. My project is about ( ISOLATED WORD speech RECOGNITION Using Hybrid SVM /HMM).

Pre-processing

The data base consists 25 speakers ,male ,female, young and child each speaker the same utter the same 20 words .

The file is saved as (*.wav);

The preprocessing includes sampling, segmentation, framing and windowing.

Sampling frequency=11025Hz

16 – Bit A/D Converter.

Framing the continuous speech signal is blocked into frames of N samples N=256(which is equivalent to23msec) .

Overlaps between frames =128;

Using Hamming window for windowing each frame.

My question is this procedure right or not???

Processing

Feature extraction

The Discrete wavelet transform(DTW) daubechies filter and pitchdetection used In order to evaluate feature vectors . Used this feature vectors as input to Hybrid SVM/HMM for training and testing system .

I will do all this pre-processing and processing steps and I have a table of feature vector for each word.

My question is this procedure right or not???

Hybrid model of SVM/HMM

The hybrid model includes two parts: training and classification. Firstly , parameters of model can be obtained by training. Secondly, it can be calculated the probability estimate by Viterbi.

But the output of SVM is numerical value. For combined with HMM easily, it should transform the value into probability .

My question how can Ido that when I used this feature vector as input to Hybrid SVM/HMM for training and testing system to recognize each word (so I needed algorithm and program to do that using matlab).

With Best Regards

Ahmed Alhamdani

27 Jan 2013 Govt college of Engg Amravati

sir i used it .i 1st enframed the input speech and then enframed signal is passed to function sbc_2...it stuck somewhere in the middle....please suggest me what changes shall i do

01 May 2009 shiv asthana  
16 Feb 2009 Amit  

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