hshi-speech Goto Github PK
Name: Hao SHI (Fumi)
Type: User
Company: Kyoto University
Bio: A speech processing beginner.
Location: Kyoto, Japan
Name: Hao SHI (Fumi)
Type: User
Company: Kyoto University
Bio: A speech processing beginner.
Location: Kyoto, Japan
This is a curated list of awesome Speech Bandwidth Extension tutorials, papers, libraries, datasets, tools, scripts and results. The purpose of this repo is to organize the world’s resources for speech bandwidth extension, and make them universally accessible and useful.
A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.
Conditional Diffusion Probabilistic Model for Speech Enhancement
This repository is developed for speech enhancement based on Conv-TasNet using ESPNet framework.
PyTorch code for our paper "Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining" (CVPR2020).
Unofficial implementation of "Prompt-to-Prompt Image Editing with Cross Attention Control" with Stable Diffusion
DCCRN with various loss functions
Code for the paper Hybrid Spectrogram and Waveform Source Separation
Deep Learning Based Monaural Speech Dereverberation Models: Hope We Can Get Better Performance of Dereverberation
This repo contains the scripts, models, and required files for the Deep Noise Suppression (DNS) Challenge.
model descriptions
Implementing the paper -
LibriMix-repo
previous created dataset
I have add some feature extraction function for torchaudio.
NOMAD is a fully unsupervised non-matching reference audio quality metric
one example of spectrogram decomposition (feature map)
accents asr
This repository contains some material of speech enhancement and dereverberation. On the one hand, I summarize this work for my further understanding. On the other hand, I hope that all beginners or masters interested in speech enhancement can ask me questions and make progress together. A lot of my summary is not very good, I hope you put forward corrections!
Self-Supervised Speech Pre-training and Representation Learning Toolkit.
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Score-based Generative Models (Diffusion Models) for Speech Enhancement and Dereverberation
TENET: A Time-reversal Enhancement Network for noise-robust ASR
This repo. is for wavs evaluation.
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