Correlated lip motion and voice audio data

This data set is comprised of correlated audio and lip movement data in multiple videos of multiple subjects reading the same text. It was collected to facilitate the development and validation of algorithms used to train and test a compound biometric system that consists of lip-motion and voice rec...

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Published inData in brief Vol. 21; pp. 856 - 860
Main Authors Colasito, Marco, Straub, Jeremy, Kotala, Pratap
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier Inc 01.12.2018
Elsevier
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Abstract This data set is comprised of correlated audio and lip movement data in multiple videos of multiple subjects reading the same text. It was collected to facilitate the development and validation of algorithms used to train and test a compound biometric system that consists of lip-motion and voice recognition. The data set is a collection of videos of volunteers reciting a fixed script that is intended to be used to train software to recognize voice and lip-motion patterns. A second video is included of the individual reciting a shorter phrase, which is designed to be used to test the recognition functionality of the system. The recordings were collected in a controlled, indoor setting with a 4K professional-grade camcorder and adjustable, LED lights.
AbstractList This data set is comprised of correlated audio and lip movement data in multiple videos of multiple subjects reading the same text. It was collected to facilitate the development and validation of algorithms used to train and test a compound biometric system that consists of lip-motion and voice recognition. The data set is a collection of videos of volunteers reciting a fixed script that is intended to be used to train software to recognize voice and lip-motion patterns. A second video is included of the individual reciting a shorter phrase, which is designed to be used to test the recognition functionality of the system. The recordings were collected in a controlled, indoor setting with a 4K professional-grade camcorder and adjustable, LED lights.
This data set is comprised of correlated audio and lip movement data in multiple videos of multiple subjects reading the same text. It was collected to facilitate the development and validation of algorithms used to train and test a compound biometric system that consists of lip-motion and voice recognition. The data set is a collection of videos of volunteers reciting a fixed script that is intended to be used to train software to recognize voice and lip-motion patterns. A second video is included of the individual reciting a shorter phrase, which is designed to be used to test the recognition functionality of the system. The recordings were collected in a controlled, indoor setting with a 4K professional-grade camcorder and adjustable, LED lights.This data set is comprised of correlated audio and lip movement data in multiple videos of multiple subjects reading the same text. It was collected to facilitate the development and validation of algorithms used to train and test a compound biometric system that consists of lip-motion and voice recognition. The data set is a collection of videos of volunteers reciting a fixed script that is intended to be used to train software to recognize voice and lip-motion patterns. A second video is included of the individual reciting a shorter phrase, which is designed to be used to test the recognition functionality of the system. The recordings were collected in a controlled, indoor setting with a 4K professional-grade camcorder and adjustable, LED lights.
Author Colasito, Marco
Kotala, Pratap
Straub, Jeremy
AuthorAffiliation a Department of Computer Science, Valdosta State University, United States
b Department of Computer Science, North Dakota State University, United States
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  organization: Department of Computer Science, Valdosta State University, United States
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  givenname: Pratap
  surname: Kotala
  fullname: Kotala, Pratap
  organization: Department of Computer Science, North Dakota State University, United States
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10.1145/30851.30874
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10.21437/Interspeech.2004-424
10.1109/TMM.2009.2030637
10.1109/TASL.2012.2201472
10.1016/j.patrec.2007.02.017
10.21437/Interspeech.2011-169
10.1007/978-3-319-54184-6_6
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10.1016/j.specom.2004.12.004
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