CHiME2 Grid

Introduction CHiME2 Grid was developed as part of The 2nd CHiME Speech Separation and Recognition Challenge and contains approximately 120 hours of English speech from a noisy living room environment. The CHiME Challenges focus on distant-microphone automatic speech recognition (ASR) in real-world environments. CHiME2 Grid reflects the small vocabulary track of the CHiME2 Challenge. The target utterances were taken from the Grid corpus and consist of 34 speakers reading simple 6-word sequences. LDC also released CHiME2 WSJ0 (LDC2017S10) and CHiME3 (LDC2017S24). Data Data is divided into training, development and test sets. All data is provided as 16 bit WAV files sampled at 16 kHz. The noisy utterances are provided both in isolated form and in embedded form. The latter either involve five seconds of background noise before and after the utterance (in the training set) or they are mixed in continuous five minute noise background recordings (in the development and test sets). Seven hours of noise background not part of the training set are also included. The data is accompanied by one annotation file per speaker that includes additional technical information. Also included is a baseline Hidden Markov Model (HMM)-based speech recogniser and a scoring tool designed for the 2nd CHiME Challenge to allow users to obtain keyword recognition scores from formatted result files, perform recognition and score the challenge data, and estimate parameters of speaker dependent HMMs. Samples Please listen to the following samples: Clean Embedded Isolated Reverberated Updates None at this time. Portions © 2017 Inria Nancy - Grand Est, University of Sheffield, Mitsubishi Electric Research Labs, Fondazione Bruno Kessler, © 2017 Trustees of the University of Pennsylvania

### 数据集简介
CHiME2 Grid 数据集是作为第二届CHiME语音分离与识别挑战赛（The 2nd CHiME Speech Separation and Recognition Challenge）的组成部分开发而成，涵盖约120小时来自嘈杂起居室环境的英语语音数据。CHiME系列挑战赛聚焦真实场景下的远场麦克风自动语音识别（ASR）任务，CHiME2 Grid 对应CHiME2挑战赛的小词汇量赛道。目标语音取自Grid语料库，由34名说话人朗读简单的6词语句构成。此外，语言数据联盟（LDC）还发布了CHiME2 WSJ0（LDC2017S10）与CHiME3（LDC2017S24）。

### 数据说明
该数据集划分为训练集、开发集与测试集。所有数据均采用16位精度、16kHz采样率的WAV格式存储。带噪语音同时提供孤立式与嵌入式两种形式：其中嵌入式形式分为两类场景，训练集的嵌入式语音会在语音片段前后各保留5秒背景噪声；开发集与测试集的嵌入式语音则将目标语音嵌入至连续5分钟的背景噪声录音中。此外还收录了不属于训练集的7小时背景噪声数据。
每名说话人对应一份标注文件，其中包含额外的技术信息。同时配套提供第二届CHiME挑战赛专用的基线隐马尔可夫模型（Hidden Markov Model, HMM）语音识别器与评分工具，可支持用户从格式化结果文件中获取关键词识别得分、完成语音识别并对挑战赛数据进行评分，以及估算与说话人相关的隐马尔可夫模型参数。

### 样例试听
请收听以下样例：纯净语音、嵌入式带噪语音、孤立式带噪语音、混响语音。

### 更新记录
目前暂无更新。

### 版权声明
本数据集部分内容 © 2017 法国国家信息与自动化研究所南希-大东部分部、谢菲尔德大学、三菱电机研究实验室、布鲁诺·凯塞勒基金会，以及2017年宾夕法尼亚大学受托人所有。

搜集汇总

背景与挑战

背景概述

CHiME2 Grid是一个包含120小时英语语音的数据集，主要用于嘈杂环境下的语音识别研究。数据包括训练、开发和测试集，提供16 kHz采样的WAV文件，并附带基线HMM识别器和评分工具，适合小词汇量语音识别任务。