AirPlay and AirPlay 2 audio player

EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine

PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models

Chinese Mandarin tts text-to-speech 中文 (普通话) 语音 合成 , by fastspeech 2 , implemented in pytorch, using waveglow as vocoder, with biaobei and aishell3 datasets

A Non-Autoregressive Transformer based Text-to-Speech, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate TTS

Two-talker Speech Separation with LSTM/BLSTM by Permutation Invariant Training method.

A Non-Autoregressive End-to-End Text-to-Speech (text-to-wav), supporting a family of SOTA unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate E2E-TTS

Adaptive and Focusing Neural Layers for Multi-Speaker Separation Problem

PyTorch Implementation of Google's Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. This implementation supports both single-, multi-speaker TTS and several techniques to enforce the robustness and efficiency of the model.

This is the official implementation of our multi-channel multi-speaker multi-spatial neural audio codec architecture.

Multi-Speaker FastSpeech2 applicable to Korean. Description about train and synthesize in detail.

Urdu Speech Recognition using Kaldi ASR, by training Triphone Acoustic GMMs using the PRUS dataset.

An Algorithm for Speaker Recognition in a Multi-Speaker Environment