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Bayesian VUS Classifier

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Bayesian VUS Classifier



20 Feb 2014 (Updated )

This exercise utilizes four programs to train a Bayesian classifier and classify frames of signals.

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This MATLAB exercise utilizes a set of four MATLAB programs to both train a Bayesian classifier (using a designated training set of 11 speech files embedded within a background of low level noise and miscellaneous acoustic effects (e.g. lip smack, pops, etc.)), and to classify frames of signal from independent test utterances as belonging to one of the three classes:
       1. Class 1 – Silence/Background
       2. Class 2 – Unvoiced Speech
       3. Class 3 – Voiced Speech
using a Bayesian statistical framework as discussed in Section 10.4 of TADSP. The feature vector associated with each frame of signal consists of five short-time speech analysis parameters, namely:
       1. short-time log energy,
       2. short-time zero crossings per 10 msec interval,
       3. normalized autocorrelation at unit sample delay,
       4. first predictor coefficient of p = 12 pole LPC analysis,
       5. normalized log prediction error of p = 12 LPC analysis.

Required Products MATLAB
MATLAB release MATLAB 8.5 (R2015a)
MATLAB Search Path
Other requirements Requires speech files and functions folder
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20 Feb 2014 1.1

Updated description

28 Feb 2014 1.2

text size on buttons made smaller

03 Mar 2014 1.3

fixed path to speech_files; edited GUI to set sampling rate to 10000 Hz

18 Apr 2014 1.4

code updates; Read_Me.txt setup file; pathnew_matlab_central example

16 Jun 2015 1.4

Updated to work with post-R2014b graphics

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