ouleiwa's Stars
flexflow/FlexFlow
FlexFlow Serve: Low-Latency, High-Performance LLM Serving
flame/how-to-optimize-gemm
NervanaSystems/maxas
Assembler for NVIDIA Maxwell architecture
sunlex0717/DissectingTensorCores
Liu-xiandong/How_to_optimize_in_GPU
This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several basic kernel optimizations, including: elementwise, reduce, sgemv, sgemm, etc. The performance of these kernels is basically at or near the theoretical limit.
dberghi/Leveraging-Visual-Supervision-for-Array-based-ASDL
Code for "Leveraging Visual Supervision for Array-based Active Speaker Detection and Localization"
FrePainter/code
brucefan1983/CUDA-Programming
Sample codes for my CUDA programming book
rishikksh20/vae_tacotron2
VAE Tacotron 2, an alternative of GST Tacotron
jinhan/tacotron2-vae
Implementation of "Learning Latent Representations for Style Control and Transfer in End-to-end Speech Synthesis"
NVIDIA/trt-samples-for-hackathon-cn
Simple samples for TensorRT programming
lucidrains/musiclm-pytorch
Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch
ming024/FastSpeech2
An implementation of Microsoft's "FastSpeech 2: Fast and High-Quality End-to-End Text to Speech"
yw0nam/Parallel_Tacotron2
facebookresearch/fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
keonlee9420/Parallel-Tacotron2
PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
ljpzzz/machinelearning
My blogs and code for machine learning. http://cnblogs.com/pinard
jaywalnut310/vits
VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
rishikksh20/LightSpeech
LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search
microsoft/NeuralSpeech
renqianluo/GBDT-NAS
GBDT-NAS
Kyubyong/g2p
g2p: English Grapheme To Phoneme Conversion
paechi/knowledge-distillation-seq
This repository implements sequence-level knowledge distillation (Kim and Rush 2016)
sigmeta/g2p-kd
Token-Level Ensemble Distillation for Grapheme-to-Phoneme Conversion
shendeguize/GooglePythonStyleGuideCN
Google Python Style Guide CN 谷歌Python代码风格指南中文翻译
open-mmlab/Amphion
Amphion (/æmˈfaɪən/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.
coqui-ai/TTS
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
yeyupiaoling/VoiceprintRecognition-Pytorch
This project uses a variety of advanced voiceprint recognition models such as EcapaTdnn, ResNetSE, ERes2Net, CAM++, etc. It is not excluded that more models will be supported in the future. At the same time, this project also supports MelSpectrogram, Spectrogram data preprocessing methods
KinglittleQ/GST-Tacotron
A PyTorch implementation of Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
vincentherrmann/pytorch-wavenet
An implementation of WaveNet with fast generation