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".

To generate the waveform demo, for paper "Wireless Standard Identification via Mel Frequency Cepstrum" in IEEE Communications Letters, vol. 26, no. 11, pp. 2656-2660, Nov. 2022

infrasonic acoustic/ elephant rumble detection using MFCC coefficients

Audio signal processing via Mel Frequency Cepstral Coefficients (MFCC) which leads to speaker recognition using MATLAB.

TP2 Métodos Numéricos Avanzados 2C 2014

MFCC Feature Extraction In Matlab

🔧 Octave functions for calculating MFCC

HW03 of Speech Processing