A 10000+ hours dataset for Chinese speech recognition

Overview

WenetSpeech

A 10000+ Hours Multi-domain Chinese Corpus for Speech Recognition

WenetSpeech

Download

Please visit the official website, read the license, and follow the instruction to download the data.

Benchmark

Toolkit Model test_net test_meeting
Kaldi Chain Model
ESPnet Joint CTC/Conformer
WeNet Joint CTC/Conformer

Description

Creation

First, we collect all the data from YouTube and Podcast; Then, OCR is used to label YouTube data, auto trancrition is used to label Podcast data; Finally, a novel end-to-end label error detection method is used to further validate and filter the data.

Categories

In summary, WenetSpeech groups all data into 3 categories, as the following table shows:

Set Hours Confidence Usage
High Label 10005 >=0.95 Supervised Training
Weak Label 2478 [0.6, 0.95] Semi-supervised or noise training
Unlabel 9952 / Unsupervised training or Pre-training
In Total 22435 / All above

High Label Data

All of the data is from Youtube and Podcast, and we tag all the data with its source and domain. We classify the data into 10 groups according to its domain,speaking style, or scenarios.

Domain Youtube Podcast Total
audiobook 0 250.9 250.9
commentary 112.6 135.7 248.3
documentary 386.7 90.5 477.2
drama 4338.2 0 4338.2
interview 324.2 614 938.2
news 0 868 868
reading 0 1110.2 1110.2
talk 204 90.7 294.7
variety 603.3 224.5 827.8
others 144 507.5 651.5
Total 6113 3892 10005

We provide 3 training subsets, namely S, M and L. Subsets S, M are sampled from all the high label data which has the oracle confidence 1.0

Training Subsets Confidence Hours
L [0.95, 1.0] 10005
M 1.0 1000
S 1.0 100

Evaluation Sets

Evaluation Sets Hours Source Description
DEV 20 Internet Specially designed for some speech tools which require cross-validation set in training
TEST_NET 23 Internet Match test
TEST_MEETING 15 Real meeting Mismatch test which is far-field, conversational, and spontaneous meeting speech

Contributors

ACKNOWLEDGEMENTS

  1. WenetSpeech referred a lot of work of GigaSpeech, including metadata design, license design, data encryption, downloading pipeline, and so on. The authors would like to thank Jiayu Du and Guoguo Chen for their suggestions on this work.
  2. The authors would like to thank my college Lianhui Zhang, Yu Mao for collecting some of the YouTube data.
Owner
Production First and Production Ready End-to-End Speech Toolkit
Simple telegram bot to convert files into direct download link.you can use telegram as a file server 🪁

TGCLOUD 🪁 Simple telegram bot to convert files into direct download link.you can use telegram as a file server 🪁 Features Easy to Deploy Heroku Supp

Mr.Acid dev 6 Oct 18, 2022
CVSS: A Massively Multilingual Speech-to-Speech Translation Corpus

CVSS: A Massively Multilingual Speech-to-Speech Translation Corpus CVSS is a massively multilingual-to-English speech-to-speech translation corpus, co

Google Research Datasets 118 Jan 06, 2023
Large-scale pretraining for dialogue

A State-of-the-Art Large-scale Pretrained Response Generation Model (DialoGPT) This repository contains the source code and trained model for a large-

Microsoft 1.8k Jan 07, 2023
A Python wrapper for simple offline real-time dictation (speech-to-text) and speaker-recognition using Vosk.

Simple-Vosk A Python wrapper for simple offline real-time dictation (speech-to-text) and speaker-recognition using Vosk. Check out the official Vosk G

2 Jun 19, 2022
File-based TF-IDF: Calculates keywords in a document, using a word corpus.

File-based TF-IDF Calculates keywords in a document, using a word corpus. Why? Because I found myself with hundreds of plain text files, with no way t

Jakob Lindskog 1 Feb 11, 2022
Deal or No Deal? End-to-End Learning for Negotiation Dialogues

Introduction This is a PyTorch implementation of the following research papers: (1) Hierarchical Text Generation and Planning for Strategic Dialogue (

Facebook Research 1.4k Dec 29, 2022
VoiceFixer VoiceFixer is a framework for general speech restoration.

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

Leo 174 Jan 06, 2023
A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.

Basic-UI-for-GPT-J-6B-with-low-vram A repository to run GPT-J-6B on low vram systems by using both ram, vram and pinned memory. There seem to be some

90 Dec 25, 2022
Utilities for preprocessing text for deep learning with Keras

Note: This utility is really old and is no longer maintained. You should use keras.layers.TextVectorization instead of this. Utilities for pre-process

Hamel Husain 180 Dec 09, 2022
本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料,该资料目前包含 自然语言处理各领域的 面试题积累。

【关于 NLP】那些你不知道的事 作者:杨夕、芙蕖、李玲、陈海顺、twilight、LeoLRH、JimmyDU、艾春辉、张永泰、金金金 介绍 本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料,该资料目前包含 自然语言处理各领域的 面试题积累。 目录架构 一、【

1.4k Dec 30, 2022
Code of paper: A Recurrent Vision-and-Language BERT for Navigation

Recurrent VLN-BERT Code of the Recurrent-VLN-BERT paper: A Recurrent Vision-and-Language BERT for Navigation Yicong Hong, Qi Wu, Yuankai Qi, Cristian

YicongHong 109 Dec 21, 2022
List of GSoC organisations with number of times they have been selected.

Welcome to GSoC Organisation Frequency And Details 👋 List of GSoC organisations with number of times they have been selected, techonologies, topics,

Shivam Kumar Jha 41 Oct 01, 2022
Simple Speech to Text, Text to Speech

Simple Speech to Text, Text to Speech 1. Download Repository Opsi 1 Download repository ini, extract di lokasi yang diinginkan Opsi 2 Jika sudah famil

Habib Abdurrasyid 5 Dec 28, 2021
Code from the paper "High-Performance Brain-to-Text Communication via Handwriting"

Code from the paper "High-Performance Brain-to-Text Communication via Handwriting"

Francis R. Willett 305 Dec 22, 2022
GPT-3 command line interaction

Writer_unblock Straight-forward command line interfacing with GPT-3. Finding yourself stuck at a conceptual stage? Spinning your wheels needlessly on

Seth Nuzum 6 Feb 10, 2022
Baseline code for Korean open domain question answering(ODQA)

Open-Domain Question Answering(ODQA)는 다양한 주제에 대한 문서 집합으로부터 자연어 질의에 대한 답변을 찾아오는 task입니다. 이때 사용자 질의에 답변하기 위해 주어지는 지문이 따로 존재하지 않습니다. 따라서 사전에 구축되어있는 Knowl

VUMBLEB 69 Nov 04, 2022
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing

Introduction Funnel-Transformer is a new self-attention model that gradually compresses the sequence of hidden states to a shorter one and hence reduc

GUOKUN LAI 197 Dec 11, 2022
Code for CodeT5: a new code-aware pre-trained encoder-decoder model.

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation This is the official PyTorch implementation

Salesforce 564 Jan 08, 2023
Local cross-platform machine translation GUI, based on CTranslate2

DesktopTranslator Local cross-platform machine translation GUI, based on CTranslate2 Download Windows Installer You can either download a ready-made W

Yasmin Moslem 29 Jan 05, 2023
✔👉A Centralized WebApp to Ensure Road Safety by checking on with the activities of the driver and activating label generator using NLP.

AI-For-Road-Safety Challenge hosted by Omdena Hyderabad Chapter Original Repo Link : https://github.com/OmdenaAI/omdena-india-roadsafety Final Present

Prathima Kadari 7 Nov 29, 2022