jefflai108/mfcc

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Created over 7 years ago
Updated over 7 years ago

jefflai108/mfcc

jefflai108

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Steps to extract mfcc features from audios

Contrastive-Predictive-Coding-PyTorch

Contrastive Predictive Coding for Automatic Speaker Verification

pytorch-kaldi-neural-speaker-embeddings

A light weight neural speaker embeddings extraction based on Kaldi and PyTorch.

ASSERT

JHU's system submission to the ASVspoof 2019 Challenge: Anti-Spoofing with Squeeze-Excitation and Residual neTworks (ASSERT).

Attentive-Filtering-Network

University of Edinbrugh-Johns Hopkins University's system for ASVspoof 2017 Version 2.0 dataset.

Unsupervised-TTS

Semi-Supervsied-Spoken-Language-Understanding-PyTorch

Semi-supervised spoken language understanding (SLU) via self-supervised speech and language model pretraining

PARP-wav2vec-PyTorch

LSTM

Voice activity detection of noisy speech files with LSTM. LSTM is implemented with Keras. Data processing is done with Python, MATLAB, and Bash. Experiments are done on Johns Hopkins CLSP GPUs.

scale

Some of my public work at https://hltcoe.jhu.edu/research/scale/scale-2017/

intro-machine-learning-paper

Paper I have read for understanding statistical machine learning and speaker recognition

noise_cancellation

Noise cancellation system for speech files with different kinds of noise.

TTS-Pruning-Pytorch

LDA

An implementation of Linear Discriminant Analysis on multi-class speaker recognition.

lexicon-learner