Machine learning, in numpy

a library for audio and music analysis

A library for audio and music analysis, feature extraction.

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

.NET DSP library with a lot of audio processing functions

🔉 spafe: Simplified Python Audio Features Extraction

A C++ Library for Audio Analysis

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can…

A suite of speech signal processing tools

Audio feature extraction and classification

🔉 👦 👧Voice based gender recognition using Mel-frequency cepstrum coefficients (MFCC) and Gaussian mixture models (GMM)

LibrosaCpp is a c++ implemention of librosa to compute short-time fourier transform coefficients,mel spectrogram or mfcc

Kaldi-compatible online & offline feature extraction with PyTorch, supporting CUDA, batch processing, chunk processing, and autograd - Provide C++ & Python API

A differentiable version of SPTK

Identify the emotion of multiple speakers in an Audio Segment

Synchronize your subtitles using machine learning

Detecting emotions using MFCC features of human speech using Deep Learning

A program for automatic speaker identification using deep learning techniques.

A simple audio feature extraction library

python codes to extract MFCC and FBANK speech features for Kaldi