Popular GitHub Repositories for Mfcc

Lyrics-to-audio-alignement system. Based on Machine Learning Algorithms: Hidden Markov Models with Viterbi forced alignment. The alignment is explicitly aware of durations of musical notes. The phonetic model are classified with MLP Deep Neural Network.

:sound: :boy: :girl: :woman: :man: Speaker identification using voice MFCCs and GMM

Deep learning using CNN for Mandarin Chinese tone classification

Deep Learning model for lexical stress detection in spoken English

In this work we propose two postprocessing approaches applying convolutional neural networks (CNNs) either in the time domain or the cepstral domain to enhance the coded speech without any modification of the codecs. The time domain approach follows an end-to-end fashion, while the cepstral domain approach uses analysis-synthesis with cepstral domain features. The proposed postprocessors in both domains are evaluated for various narrowband and wideband speech codecs in a wide range of conditions. The proposed postprocessor improves speech quality (PESQ) by up to 0.25 MOS-LQO points for G.711, 0.30 points for G.726, 0.82 points for G.722, and 0.26 points for adaptive multirate wideband codec (AMR-WB). In a subjective CCR listening test, the proposed postprocessor on G.711-coded speech exceeds the speech quality of an ITU-T-standardized pos

[wip]Speech recognition tool-box written by Nim. Based on Arraymancer.

Voice Alignment and Conversion with Neural Networks and the WORLD codec.

基于GMM与MFCC特征进行数字0-9的语音识别，GMM，MFCC，语音识别，中文数据，sklearn，Digital Voice Recognition。

Identifying individual speakers in an audio stream based on the unique characteristics found in individual voices using Python

基于HMM与MFCC特征进行数字0-9的语音识别，HMM，GMMHMM，MFCC，语音识别，sklearn，Digital Voice Recognition。

Recognizing common speech commands using Keras and Tensorflow.

Music genre classification using deep learning

This folder will be all about extracting features of speech / voice / sound using python

Building a speaker identification & verification pipeline for Vietnamese voices :sleepy:

This repository is based on my research work "Detecting Freezing of Gait in Parkinson's Disease Patients Using Multi-Modal Machine Learning"

Emotion Recognition in Speech: This project leverages advanced machine learning techniques to classify emotions from speech using the Toronto Emotional Speech Set (TESS). By extracting Mel-Frequency Cepstral Coefficients (MFCC) and utilizing an LSTM-based deep learning model, the project accurately identifies emotions like anger, happiness, and sad

[????] COVID-19 ?? AI ?? ??