ouleiwa

ouleiwa's Stars

• flexflow/FlexFlow

  FlexFlow Serve: Low-Latency, High-Performance LLM Serving

  Language:C++1.6k223

• flame/how-to-optimize-gemm

  Language:C1.7k351

• NervanaSystems/maxas

  Assembler for NVIDIA Maxwell architecture

  Language:Sass941160

• sunlex0717/DissectingTensorCores

  Language:Cuda7016

• 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.

  Language:Cuda790124

• dberghi/Leveraging-Visual-Supervision-for-Array-based-ASDL

  Code for "Leveraging Visual Supervision for Array-based Active Speaker Detection and Localization"

  Language:Python41

• FrePainter/code

  Language:Python205

• brucefan1983/CUDA-Programming

  Sample codes for my CUDA programming book

  Language:Cuda1.5k315

• rishikksh20/vae_tacotron2

  VAE Tacotron 2, an alternative of GST Tacotron

  Language:Python8529

• jinhan/tacotron2-vae

  Implementation of "Learning Latent Representations for Style Control and Transfer in End-to-end Speech Synthesis"

  Language:Jupyter Notebook16733

• NVIDIA/trt-samples-for-hackathon-cn

  Simple samples for TensorRT programming

  Language:Python1.5k334

• lucidrains/musiclm-pytorch

  Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch

  Language:Python3.1k249

• ming024/FastSpeech2

  An implementation of Microsoft's "FastSpeech 2: Fast and High-Quality End-to-End Text to Speech"

  Language:Python1.7k523

• yw0nam/Parallel_Tacotron2

  Language:Python73

• facebookresearch/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  Language:Python30.1k6.4k

• keonlee9420/Parallel-Tacotron2

  PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

  Language:Python18744

• ljpzzz/machinelearning

  My blogs and code for machine learning. http://cnblogs.com/pinard

  Language:Jupyter Notebook8.2k3.7k

• jaywalnut310/vits

  VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

  Language:Python6.6k1.2k

• rishikksh20/LightSpeech

  LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search

  Language:Python807

• microsoft/NeuralSpeech

  Language:Python1.4k182

• renqianluo/GBDT-NAS

  GBDT-NAS

  Language:Python285

• Kyubyong/g2p

  g2p: English Grapheme To Phoneme Conversion

  Language:Python783126

• paechi/knowledge-distillation-seq

  This repository implements sequence-level knowledge distillation (Kim and Rush 2016)

  Language:Jupyter Notebook3

• sigmeta/g2p-kd

  Token-Level Ensemble Distillation for Grapheme-to-Phoneme Conversion

  Language:Python201

• shendeguize/GooglePythonStyleGuideCN

  Google Python Style Guide CN 谷歌Python代码风格指南中文翻译

  18757

• 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.

  Language:Python4.4k373

• coqui-ai/TTS

  🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

  Language:Python33k4k

• 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

  Language:Python735116

• KinglittleQ/GST-Tacotron

  A PyTorch implementation of Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis

  Language:Python35672

• vincentherrmann/pytorch-wavenet

  An implementation of WaveNet with fast generation

  Language:Jupyter Notebook961225