Functions for creating speech features in MATLAB.
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Updated
Jul 7, 2020 - MATLAB
Functions for creating speech features in MATLAB.
Maltab code for extraction of Mel Frequency Cepstral Coefficients
Voice recognition system that distinguishes both user identity and voice content.
Voice Activity Detection and signal segmentation in time windows. Feature extraction in time and frequency domain. Classification in ten individual speakers.
Using MFCC features on Speech Signals to classify Digits after matching templates by DTW. Course project at IIT Guwahati.
Mel Frequency Cepstral Coefficients (MFCCs) are a feature widely used in automatic speech and speaker recognition. They were introduced by Davis and Mermelstein in the 1980s, and have been state-of-the-art ever since. In this project, we have implemented MFCC feature extraction in Matlab.
Implementing gender recognition based on first 14 MFCC coefficients, pitch period, short time energy and spectral centroid
Persian music classification
This repository is for the Final Project for DSAP1718
MATLAB code for audio signal processing, emphasizing Real Cepstrum and MFCC feature extraction. Reads a wave file, applies Hamming and Rectangular windows, then computes Real Cepstrum. Utilizes MATLAB's built-in functions for extracting MFCC features. Perfect for audio analysis and feature engineering.
Repository for source code from my enginner's degree thesis: "GUI Toolbox for sound processing".
infrasonic acoustic/ elephant rumble detection using MFCC coefficients
Audio signal processing via Mel Frequency Cepstral Coefficients (MFCC) which leads to speaker recognition using MATLAB.
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