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-evaluation-metrics-used-for-the-performance-evaluation-of-voice-conversion-vc-models

Evaluation Metrics Used For The Performance Evaluation of Voice Conversion (VC) Models

algan-vc-generated-audio-samples

Generated Audio Samples by ALGAN-VC model are available in the folder

all-programming-e-books-pdf

A Curated List Of Programming Books For C, C++ , Python, JavaScript, NodeJs, ReactJs, Web, JQuery, Flask, Dom, Angular, CSS, HTML for beginners, intermediate, advanced and experts

arabic-asr-system

automated speech recognition system for arabic language for customers query classification, with adaptive learning and merged learning models trained with weka

arabic-speech-recognition

This repository contains my attempt to use two famous speech recognition frameworks (Kaldi, CMU Sphinx4) for Arabic Language using the publicly-available dataset "Arabic Corpus of Isolated Words"

audio_course_project

Project done as part of Audio Processing course at Tampere University. Topic was separation of harmonic and percussive elements according to paper EPARATION OF A MONAURAL AUDIO SIGNAL INTO HARMONIC/PERCUSSIVE COMPONENTS BY COMPLEMENTARY DIFFUSION ON SPECTROGRAM by Nobutaka Ono, Kenichi Miyamoto, Jonathan Le Roux, Hirokazu Kameoka, and Shigeki Sagayama.

audiomentations

A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.

autovc

cargan

Official repository for the paper "Chunked Autoregressive GAN for Conditional Waveform Synthesis"

chained-encoder-decoder-predictor

change-emotions

Nonparallel Emotional Speech Conversion with MUNIT. Introduction: This is a tensorflow implementation of paper(https://arxiv.org/pdf/1811.01174.pdf) Nonparallel Emotional Speech Conversion. It is an end-to-end voice conversion system which can change the speaker's emotion. For example, neutral to angry, sad to happy. The model aims at generating speech with desired emotions while keeping the original linguistic content and speaker identity. It first extracts acoustic features from raw audio, then learn the mapping from source emotion to target emotion in the feature space, and finally put those features together to rebuild the waveform. In our approach, three types of features are considered: Features: Fundamental frequency (log F_0), converted by logarithm Gaussian normalized transformation Power envelope, converted by logarithm Gaussian normalized transformation Mel-cepstral coefficients (MCEPs), a representation of spectral envelope, trained by CycleGAN Aperiodicities (APs), directly used without modification. Dependencies: Python 3.5, Numpy 1.15, TensorFlow 1.8, LibROSA 0.6, FFmpeg 4.0, PyWorld

code

Compilation of R and Python programming codes on the Data Professor YouTube channel.

controllable_evc_code

This is the code for controllable EVC framework for seen and unseen emotion generation.

coursera-deep-learning

My notes / works on deep learning from Coursera

crank

A toolkit for non-parallel voice conversion based on vector-quantized variational autoencoder

cycle_gan_vc

Reproducing PARALLEL-DATA-FREE VOICE CONVERSION USING CYCLE-CONSISTENT ADVERSARIAL NETWORKS (https://arxiv.org/pdf/1711.11293.pdf)

cyclegan

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

cyclegan-emovc

EMOTIONAL VOICE CONVERSION WITH CYCLE-CONSISTENT ADVERSARIAL NETWORK

cyclegan-tensorflow

Tensorflow implementation for learning an image-to-image translation without input-output pairs. https://arxiv.org/pdf/1703.10593.pdf

cycletransgan-evc

CycleTransGAN-EVC: A CycleGAN-based Emotional Voice Conversion Model with Transformer

d2l-tvm

Dive into Deep Learning Compiler

deep-learning

Course: Deep Learning

deep-learning-model-convertor

The convertor/conversion of deep learning models for different deep learning frameworks/softwares.

deep-learning-roadmap

:satellite: All You Need to Know About Deep Learning - A kick-starter

deeplearningexamples

Deep Learning Examples

deepnude-an-image-to-image-technology

DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络（GAN,Generative Adversarial Network）图像生成的理论与实践研究。

dl-for-emo-tts

:computer: :robot: A summary on our attempts at using Deep Learning approaches for Emotional Text to Speech :speaker:

dyganvc

demo page https://MingjieChen.github.io/dygan-vc

ecapa-tdnn

Unofficial reimplementation of ECAPA-TDNN for speaker recognition (EER=0.86 for Vox1_O when train only in Vox2)

emo-stargan

Implementation of Emo-StarGAN