A Tensorflow Implementation of the FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
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Updated
Aug 12, 2020
A Tensorflow Implementation of the FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
AdaSpeech: Adaptive Text to Speech for Custom Voice
LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search
Refactored version of https://github.com/ming024/FastSpeech2
PAddle PARAllel text-to-speech toolKIT (supporting Tacotron2, Transformer TTS, FastSpeech2/FastPitch, SpeedySpeech, WaveFlow and Parallel WaveGAN)
An Android application that allows visually impaired people to hear which bus lines are passing next to them.
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 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
An implementation of Microsoft's "AdaSpeech: Adaptive Text to Speech for Custom Voice"
PyTorch Implementation of FastSpeech 2 : Fast and High-Quality End-to-End Text to Speech
homework for deep generation. Combine FastSpeech2 with different vocoders ⭐REFERENCE (modify origin repos): https://github.com/ming024/FastSpeech2 https://github.com/NVIDIA/waveglow https://github.com/mindslab-ai/univnet https://github.com/jik876/hifi-gan
Multi-Speaker FastSpeech2 applicable to Korean. Description about train and synthesize in detail.
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
An Android application that acts as a speaking assistant for the hearing impaired people.
Multi-Speaker Pytorch FastSpeech2: Fast and High-Quality End-to-End Text to Speech ✊
Desktop application for neural speech synthesis written in C++
This repository contain the code of the main part of my master thesis degree at Politecnico di Torino in Data science & Engineering
The Implementation of FastSpeech2 Based on Pytorch.
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