Audio feature extraction and classification
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Updated
Jul 6, 2023 - Python
Audio feature extraction and classification
A RESTFUL API implementation of an authentification system using voice fingerprint
The project presents an SVM model trained to distinguish between Real human voices and AI-generated voices.
Java Implementation of the Sonopy Audio Feature Extraction Library by MycroftAI
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
An automatic speaker recognition system built from digital signal processing tools, Vector Quantization and LBG algorithm
👉 This repository contains basic audio 🔊 processing code with feature extraction explained. 🎶 🎶 🎶
Tackle accent classification and conversion using audio data, leveraging MFCCs and spectrograms. Models differentiate accents and convert audio between accents
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.
A machine learning pipeline for stress detection from speech using acoustic feature extraction and classical classification models.
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.
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
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.
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