CHiME2 Grid
Version: 1 – Released: Thu Apr 27 13:50:11 PDT 2017
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Data Citation
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Data Citation Details
TitleCHiME2 Grid
Study Global IDhdl:11272/GJ8WY
Other IDLinguistic Data Consortium: LDC2017S07; ISBN: 1-58563-796-3; ISLRN: 134-467-387-379-1
AuthorsVincent, Emmanuel; Barker, Jon; Watanabe, Shinji; Le Roux, Jonathan; Nesta, Francesco; Matassoni, Marco
ProducerLinguistic Data Consortium (LDC), University of Pennsylvania
Production DateApril 17, 2017
Production PlacePhiladelphia
DistributorLinguistic Data Consortium (LDC), University of Pennsylvania
Deposit DateApril 27, 2017
SeriesLDC, Linguistic Data Consortium
Versionv1.0, April 17, 2017
Original Dataverse
Description and Scope


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.


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.

Description DateApril 17, 2017
KeywordsLinguistics (ACV)
Time Period Covered2017 - 2017
Date of Collection2017 - 2017
Country/NationUnited States (US); France (FR); United Kingdom (GB); Japan (JP); Italy (IT)
Kind of DataLinguistic data
Data Collection / Methodology
Data SourcesMicrophone speech
Data Availability
Number of Files 15
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Other Information
NotesInfo (DCMI type) Sound; Info (Sample type) pcm; Info (Sample rate) 16000; Info (Application) Speech recognition; Info (Language) English; Info (Language ID) eng
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"CHiME2 Grid", hdl:11272/GJ8WY