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Title:The Multi-Channel Wall Street Journal Audio Visual Corpus (MC-WSJ-AV): Specification and Initial Experiments
Authors: Michael Lincoln ; Iain McCowan ; Jithendra Vepa ; Hari Krishan Maganti
Date: 2005
Publication Title:IEEE Automatic Speech Recognition And Understanding Workshop
Publication Type:Conference Paper Publication Status:Published
Page Nos:357-362
DOI:10.1109/ASRU.2005.1566470 ISBN/ISSN:0-7803-9478-x
The recognition of speech in meetings poses a number of challenges to current Automatic Speech Recognition (ASR) techniques. Meetings typically take place in rooms with non-ideal acoustic conditions and significant background noise, and may contain large sections of overlapping speech. In such circumstances, headset microphones have to date provided the best recognition performance, however participants are often reluctant to wear them. Microphone arrays provide an alternative to close-talking microphones by providing speech enhancement through directional discrimination. Unfortunately, however, development of array front-end systems for state-of-the-art large vocabulary continuous speech recognition suffers from a lack of necessary resources, as most available speech corpora consist only of single-channel recordings. This paper describes the collection of an audio-visual corpus of read speech from a number of instrumented meeting rooms. The corpus, based on the WSJCAM0 database, is suitable for use in continuous speech recognition experiments and is captured using a variety of microphones, including arrays, as well as close-up and wider angle cameras. The paper also describes some initial ASR experiments on the corpus comparing the use of close-talking microphones with both a fixed and a blind array beamforming technique.
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Bibtex format
author = { Michael Lincoln and Iain McCowan and Jithendra Vepa and Hari Krishan Maganti },
title = {The Multi-Channel Wall Street Journal Audio Visual Corpus (MC-WSJ-AV): Specification and Initial Experiments},
book title = {IEEE Automatic Speech Recognition And Understanding Workshop},
publisher = {IEEE},
year = 2005,
pages = {357-362},
doi = {10.1109/ASRU.2005.1566470},

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