Stars
University of Edinbrugh-Johns Hopkins University's system for ASVspoof 2017 Version 2.0 dataset.
JHU's system submission to the ASVspoof 2019 Challenge: Anti-Spoofing with Squeeze-Excitation and Residual neTworks (ASSERT).
This is an open source project (formerly named Listen, Attend and Spell - PyTorch Implementation) for end-to-end ASR implemented with Pytorch, the well known deep learning toolkit.
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
Speech Signal Processing - C++ port of a subset of the Python library SSP
Speech Signal Processing - a small collection of routines in Python to do signal pr F6E9 ocessing
🏋️ Python / Modern C++ Solutions of All 3555 LeetCode Problems (Weekly Update)
🤖 💬 Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Python Implementation of Reinforcement Learning: An Introduction
This is a pytorch implementation of the paper: StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks
Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)
A curated list of speech and natural language processing resources
Facebook AI Research's Automatic Speech Recognition Toolkit
A PyTorch Implementation of End-to-End Models for Speech-to-Text
Image-to-Image Translation in PyTorch
kaldi-asr/kaldi is the official location of the Kaldi project.
Conditional WaveGAN: Generating audio samples conditioned on class labels
All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN
Real-time full-duplex speech recognition server, based on the Kaldi toolkit and the GStreamer framwork.
A humble SublimeText package for exporting highlighted code as RTF or HTML
Voice Converter Using CycleGAN and Non-Parallel Data