VoiceFixer VoiceFixer is a framework for general speech restoration.

Overview

Open In Colab PyPI version

VoiceFixer

VoiceFixer is a framework for general speech restoration. We aim at the restoration of severly degraded speech and historical speech.

46dPxJ.png

Paper

⚠️ We submit this paper to ICLR2022. Preprint on arxiv will be available before Oct.03 2021!

Usage

⚠️ Still working on it, stay tuned! Expect to be available before 2021.09.30.

Environment

# Download dataset and prepare running environment
source init.sh 

Train from scratch

Let's take VF_UNet(voicefixer with unet as analysis module) as an example. Other model have the similar training and evaluation logic.

cd general_speech_restoration/voicefixer/unet
source run.sh

After that, you will get a log directory that look like this

├── unet
│   └── log
│       └── 2021-09-27-xxx
│           └── version_0
│               └── checkpoints
                    └──epoch=1.ckpt
│               └── code

Evaluation

Automatic evaluation and generate .csv file for the results.

cd general_speech_restoration/voicefixer/unet
# Basic usage
python3 handler.py  -c <str, path-to-checkpoint> \
                    -t <str, testset> \ 
                    -l <int, limit-utterance-number> \ 
                    -d <str, description of this evaluation> \ 

For example, if you like to evaluate on all testset. And each testset you intend to limit the number to 10 utterance.

python3 handler.py  -c  log/2021-09-27-xxx/version_0/checkpoints/epoch=1.ckpt \
                    -t  base \ 
                    -l  10 \ 
                    -d  ten_utterance_for_each_testset \ 

There are generally seven testsets:

  • base: all testset
  • clip: testset with speech that have clipping threshold of 0.1, 0.25, and 0.5
  • reverb: testset with reverberate speech
  • general_speech_restoration: testset with speech that contain all kinds of random distortions
  • enhancement: testset with noisy speech
  • speech_super_resolution: testset with low resolution speech that have sampling rate of 2kHz, 4kHz, 8kHz, 16kHz, and 24kHz.

Demo

Demo page

Demo page contains comparison between single task speech restoration, general speech restoration, and voicefixer.

Pip package

We wrote a pip package for voicefixer.

Colab

You can try voicefixer using your own voice on colab!

real-life-example real-life-example real-life-example

Project Structure

.
├── dataloaders 
│   ├── augmentation # code for speech data augmentation.
│   └── dataloader # code for different kinds of dataloaders.
├── datasets 
│   ├── datasetParser # code for preparing each dataset
│   └── se # Dataset for speech enhancement (source init.sh)
│       ├── RIR_44k # Room Impulse Response 44.1kHz
│       │   ├── test
│       │   └── train
│       ├── TestSets # Evaluation datasets
│       │   ├── ALL_GSR # General speech restoration testset
│       │   │   ├── simulated
│       │   │   └── target
│       │   ├── DECLI # Speech declipping testset
│       │   │   ├── 0.1 # Different clipping threshold
│       │   │   ├── 0.25
│       │   │   ├── 0.5
│       │   │   └── GroundTruth
│       │   ├── DENOISE # Speech enhancement testset
│       │   │   └── vd_test
│       │   │       ├── clean_testset_wav
│       │   │       └── noisy_testset_wav
│       │   ├── DEREV # Speech dereverberation testset
│       │   │   ├── GroundTruth
│       │   │   └── Reverb_Speech
│       │   └── SR # Speech super resolution testset
│       │       ├── GroundTruth
│       │       └── cheby1
│       │           ├── 1000 # Different cutoff frequencies
│       │           ├── 12000
│       │           ├── 2000
│       │           ├── 4000
│       │           └── 8000
│       ├── vd_noise # Noise training dataset
│       └── wav48 # Speech training dataset
│           ├── test # Not used, included for completeness
│           └── train 
├── evaluation # The code for model evaluation
├── exp_results # The Folder that store evaluation result (in handler.py).
├── general_speech_restoration # GSR 
│   ├── unet # GSR_UNet
│   │   └── model_kqq_lstm_mask_gan
│   └── voicefixer # Each folder contains the training entry for each model.
│       ├── dnn # VF_DNN
│       ├── lstm # VF_LSTM
│       ├── unet # VF_UNet
│       └── unet_small # VF_UNet_S
├── resources 
├── single_task_speech_restoration # SSR
│   ├── declip_unet # Declip_UNet
│   ├── derev_unet # Derev_UNet
│   ├── enh_unet # Enh_UNet
│   └── sr_unet # SR_UNet
├── tools
└── callbacks

Citation

⚠️ Will be available once the paper is ready.

Enterprise Scale NLP with Hugging Face & SageMaker Workshop series

Workshop: Enterprise-Scale NLP with Hugging Face & Amazon SageMaker Earlier this year we announced a strategic collaboration with Amazon to make it ea

Philipp Schmid 161 Dec 16, 2022
Python utility library for compositing PDF documents with reportlab.

pdfdoc-py Python utility library for compositing PDF documents with reportlab. Installation The pdfdoc-py package can be installed directly from the s

Michael Gale 1 Jan 06, 2022
AllenNLP integration for Shiba: Japanese CANINE model

Allennlp Integration for Shiba allennlp-shiab-model is a Python library that provides AllenNLP integration for shiba-model. SHIBA is an approximate re

Shunsuke KITADA 12 Feb 16, 2022
Code for the paper "BERT Loses Patience: Fast and Robust Inference with Early Exit".

Patience-based Early Exit Code for the paper "BERT Loses Patience: Fast and Robust Inference with Early Exit". NEWS: We now have a better and tidier i

Kevin Canwen Xu 54 Jan 04, 2023
Header-only C++ HNSW implementation with python bindings

Hnswlib - fast approximate nearest neighbor search Header-only C++ HNSW implementation with python bindings. NEWS: version 0.6 Thanks to (@dyashuni) h

2.3k Jan 05, 2023
My implementation of Safaricom Machine Learning Codility test. The code has bugs, logical I guess I made errors and any correction will be appreciated.

Safaricom_Codility Machine Learning 2022 The test entails two questions. Question 1 was on Machine Learning. Question 2 was on SQL I ran out of time.

Lawrence M. 1 Mar 03, 2022
Extract city and country mentions from Text like GeoText without regex, but FlashText, a Aho-Corasick implementation.

flashgeotext ⚡ 🌍 Extract and count countries and cities (+their synonyms) from text, like GeoText on steroids using FlashText, a Aho-Corasick impleme

Ben 57 Dec 16, 2022
SimCSE: Simple Contrastive Learning of Sentence Embeddings

SimCSE: Simple Contrastive Learning of Sentence Embeddings This repository contains the code and pre-trained models for our paper SimCSE: Simple Contr

Princeton Natural Language Processing 2.5k Jan 07, 2023
Source code of the "Graph-Bert: Only Attention is Needed for Learning Graph Representations" paper

Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We

14 Mar 25, 2022
A Fast Command Analyser based on Dict and Pydantic

Alconna Alconna 隶属于ArcletProject, 在Cesloi内有内置 Alconna 是 Cesloi-CommandAnalysis 的高级版,支持解析消息链 一般情况下请当作简易的消息链解析器/命令解析器 文档 暂时的文档 Example from arclet.alcon

19 Jan 03, 2023
Code for "Semantic Role Labeling as Dependency Parsing: Exploring Latent Tree Structures Inside Arguments".

Code for "Semantic Role Labeling as Dependency Parsing: Exploring Latent Tree Structures Inside Arguments".

Yu Zhang 50 Nov 08, 2022
Awesome-NLP-Research (ANLP)

Awesome-NLP-Research (ANLP)

Language, Information, and Learning at Yale 72 Dec 19, 2022
Grading tools for Advanced NLP (11-711)Grading tools for Advanced NLP (11-711)

Grading tools for Advanced NLP (11-711) Installation You'll need docker and unzip to use this repo. For docker, visit the official guide to get starte

Hao Zhu 2 Sep 27, 2022
neural network based speaker embedder

Content What is deepaudio-speaker? Installation Get Started Model Architecture How to contribute to deepaudio-speaker? Acknowledge What is deepaudio-s

20 Dec 29, 2022
NeoDays-based tileset for the roguelike CDDA (Cataclysm Dark Days Ahead)

NeoDaysPlus Reduced contrast, expanded, and continuously developed version of the CDDA tileset NeoDays that's being completed with new sprites for mis

0 Nov 12, 2022
ConvBERT-Prod

ConvBERT 目录 0. 仓库结构 1. 简介 2. 数据集和复现精度 3. 准备数据与环境 3.1 准备环境 3.2 准备数据 3.3 准备模型 4. 开始使用 4.1 模型训练 4.2 模型评估 4.3 模型预测 5. 模型推理部署 5.1 基于Inference的推理 5.2 基于Serv

yujun 7 Apr 08, 2022
SurvTRACE: Transformers for Survival Analysis with Competing Events

⭐ SurvTRACE: Transformers for Survival Analysis with Competing Events This repo provides the implementation of SurvTRACE for survival analysis. It is

Zifeng 13 Oct 06, 2022
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

Weitang Liu 1.6k Jan 03, 2023
Smart discord chatbot integrated with Dialogflow to manage different classrooms and assist in teaching!

smart-school-chatbot Smart discord chatbot integrated with Dialogflow to interact with students naturally and manage different classes in a school. De

Tom Huynh 5 Oct 24, 2022
Simple Text-To-Speech Bot For Discord

Simple Text-To-Speech Bot For Discord This is a very simple TTS bot for discord made with python. For this bot you need FFMPEG, see installation to se

1 Sep 26, 2022