Implementation of Neural Voice Cloning with Few Samples Research Paper by Baidu
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Updated
Feb 23, 2021 - Python
Implementation of Neural Voice Cloning with Few Samples Research Paper by Baidu
End-2-end speech synthesis with recurrent neural networks
Recurrent Neural Network for generating piano MIDI-files from audio (MP3, WAV, etc.)
This repository contains PyTorch implementation of 4 different models for classification of emotions of the speech.
CNN 1D vs 2D audio classification
A simple audio feature extraction library
Urban sound source tagging from an aggregation of four second noisy audio clips via 1D and 2D CNN (Xception)
Zafar's Audio Functions in Matlab for audio signal analysis: STFT, inverse STFT, mel filterbank, mel spectrogram, MFCC, CQT kernel, CQT spectrogram, CQT chromagram, DCT, DST, MDCT, inverse MDCT.
Zafar's Audio Functions in Python for audio signal analysis: STFT, inverse STFT, mel filterbank, mel spectrogram, MFCC, CQT kernel, CQT spectrogram, CQT chromagram, DCT, DST, MDCT, inverse MDCT.
A librosa STFT/Fbank/mfcc feature extration written up in PyTorch using 1D Convolutions.
Linear Prediction Coefficients estimation from mel-spectrogram implemented in Python based on Levinson-Durbin algorithm.
Least-squares (sparse) spectral estimation and (sparse) LPV spectral decomposition.
Deep Multi-Speech model
Open Source Implementation of Neural Voice Cloning with Few Audio Samples (Baidu Research)
Cough detection with Log Mel Spectrogram, Wavelet Transform, Deep learning and Transfer learning techniques
This Model analyzes and predicts the input sound and then using pretrained ANC systems cancels the input sound.
Easier audio-based machine learning with TensorFlow.
Attention-based Hybrid CNN-LSTM and Spectral Data Augmentation for COVID-19 Diagnosis from Cough Sound
Framework for one-shot multispeaker system based on Deep Learning
Speech Recognition and Voice Activity Detection using a Convolutional Neural Network Architecture built with Tensorflow.js
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