xingxy's repositories

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wavenet_vocoder

WaveNet vocoder

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tacotron-tts-cpp

Tacotron text to speech in C++(synthesize only)

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Voice_Converter_CycleGAN

Voice Converter Using CycleGAN and Non-Parallel Data

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WebRtc_noise_suppression

This is WebRtc noise suppression module demo.

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blow

Code to train and run Blow

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WebRTC_deNoise

Single Channel Noise Suppression based on WebRTC

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git_learning

learn how to use git

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git

Git Source Code Mirror - This is a publish-only repository and all pull requests are ignored. Please follow Documentation/SubmittingPatches procedure for any of your improvements.

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prosody

Helsinki Prosody Corpus and A System for Predicting Prosodic Prominence from Text

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rnnoise

Recurrent neural network for audio noise reduction

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DeepLearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06

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MOSNet

Implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion"

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CDVAE-GAN-CLS-Demo

Demo page for CDVAE extended with GAN and adversarial classifier (CLS)

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self-attention-tacotron

An implementation of "Investigation of enhanced Tacotron text-to-speech synthesis systems with self-attention for pitch accent language" https://arxiv.org/abs/1810.11960

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autovc-demo

AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss

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normalise

A module for normalising text.

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lihang_book_algorithm

致力于将李航博士《统计学习方法》一书中所有算法实现一遍

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LPCNet

Efficient neural speech synthesis

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tacotron

A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)

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git-recipes

🥡 Git recipes in Chinese by Zhongyi Tong. 高质量的Git中文教程.

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tensorflow_cpp

C and C++ examples for tensorflow

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speech-aligner

speech-aligner,是一个从“人声语音”及其“语言文本”,产生音素级别时间对齐标注的工具。speech-aligner, is a tool that generate phoneme-level alignment between human speech and its transcription

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PRML

PRML algorithms implemented in Python

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Voice-Conversion-GAN

Voice Conversion using Cycle GAN's For Non-Parallel Data

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