mfcc-features

Voice Activity Detection based on Deep Learning & TensorFlow

Audio feature extraction and classification

Repository for CIKM 2020 resource track paper: MAEC: A Multimodal Aligned Earnings Conference Call Dataset for Financial Risk Prediction

Tiny Machine Learning Snoring Detection Model for Embedded devices - Adriana Rotaru

Using a raspberry pi, we listen to the coffee machine and count the number of coffee consumption

stm32-speech-recognition-and-traduction is a project developed for the Advances in Operating Systems exam at the University of Milan (academic year 2020-2021). It implements a speech recognition and speech-to-text translation system using a pre-trained machine learning model running on the stm32f407vg microcontroller.

Voice Activity Detector based on MFCC features and DNN model

Multi-class audio classification with MFCC features using CNN

A RESTFUL API implementation of an authentification system using voice fingerprint

Detect alcohol induced intoxication level from a voice sample

A Python implementation of STFT and MFCC audio features from scratch

MFCC features + SVM for speech emotion classification

Java Implementation of the Sonopy Audio Feature Extraction Library by MycroftAI

A voice authentication system leveraging Deep4SNet for DeepFake detection and GMM UBM for speaker verification. It provides a robust solution for securing voice-based authentication applications.

Implementation of Mel-Frequency Cepstral Coefficients (MFCC) extraction

Deep learning-based audio spoofing attack detection experiments for speaker verification.

A corpus that can be used to train English-to-Italian End-to-End Speech-to-Text Machine Translation models

Audio classification using a simple SVM classifier making use of MFCC and Spectrogram features coded from scratch

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