Audio feature extraction and classification

A RESTFUL API implementation of an authentification system using voice fingerprint

Java Implementation of the Sonopy Audio Feature Extraction Library by MycroftAI

The project presents an SVM model trained to distinguish between Real human voices and AI-generated voices.

An automatic speaker recognition system built from digital signal processing tools, Vector Quantization and LBG algorithm

Implementation of Mel-Frequency Cepstral Coefficients (MFCC) extraction

Feature extraction from sound signals along with complete CNN model and evaluations using tensorflow, keras and, librosa for MFCC generation

Tackle accent classification and conversion using audio data, leveraging MFCCs and spectrograms. Models differentiate accents and convert audio between accents

👉 This repository contains basic audio 🔊 processing code with feature extraction explained. 🎶 🎶 🎶

Implementação do algoritmo de extração de características em dart.

Noise classifier based on augmented UrbanSound8K.

Project I carried out during my Machine Learning course in the Master.

infrasonic acoustic/ elephant rumble detection using MFCC coefficients

SVM model using i-vector

University Course Assignments - Speech Signal Prcessing

mfcc extractor It is a simple Mel Frequency Cepstrum Coefficient extractor tool.

This repository implements a deep learning-based voice number authentication system using CNN and a Siamese Network. It verifies spoken numbers by comparing voice embeddings to reference samples. The model extracts audio features (MFCC, spectrogram) using CNN and determines similarity through a Siamese architecture.

procedures from Librosa library (https://github.com/librosa/librosa) for mfcc embeddings calculation of sound files for Raspberry Pi 64bit OS

Model untuk Project Tugas Akhir (Skripsi), berupa website rekomendasi musik dengan AI, berdasarkan deteksi genre musik & emosi pengguna

MFCCs extractor utilizing TarsosDSP library and save the results into .h5 file for further use.