The 2016 speakers in thewild speaker recognition evaluation

The newly collected Speakers in the Wild (SITW) database was central to a text-independent speaker recognition challenge held as part of a special session at Interspeech 2016. The SITW database is composed of audio recordings from 299 speakers collected from open source media, with an average of 8 s...

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Detalles Bibliográficos
Autores principales:	McLaren, M., Ferrer, L., Castan, D., Lawson, A., Morgan N., Georgiou P., Narayanan S., Metze F., Amazon Alexa; Apple; eBay; et al.; Google; Microsoft
Formato:	CONF
Materias:	Evaluation Speaker recognition Speakers in the wild database Audio recordings Character recognition Database systems Speech communication Speech processing Acoustic conditions Evaluation results Future research directions International team Speaker recognition evaluations Text independents Speech recognition
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_2308457X_v08-12-September-2016_n_p823_McLaren
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_2308457X_v08-12-September-2016_n_p823_McLaren
record_format	dspace
spelling	todo:paper_2308457X_v08-12-September-2016_n_p823_McLaren2023-10-03T16:40:52Z The 2016 speakers in thewild speaker recognition evaluation McLaren, M. Ferrer, L. Castan, D. Lawson, A. Morgan N. Georgiou P. Morgan N. Narayanan S. Metze F. Amazon Alexa; Apple; eBay; et al.; Google; Microsoft Evaluation Speaker recognition Speakers in the wild database Audio recordings Character recognition Database systems Speech communication Speech processing Acoustic conditions Evaluation Evaluation results Future research directions International team Speaker recognition Speaker recognition evaluations Text independents Speech recognition The newly collected Speakers in the Wild (SITW) database was central to a text-independent speaker recognition challenge held as part of a special session at Interspeech 2016. The SITW database is composed of audio recordings from 299 speakers collected from open source media, with an average of 8 sessions per speaker. The recordings contain unconstrained or "wild" acoustic conditions, rarely found in large speaker recognition datasets, and multi-speaker recordings for both speaker enrollment and verification. This article provides details of the SITW speaker recognition challenge and analysis of evaluation results. There were 25 international teams involved in the challenge of which 11 teams participated in an evaluation track. Teams were tasked with applying existing and novel speaker recognition algorithms to the challenges associated with the real world conditions of SITW. We provide an analysis of some of the top performing systems submitted during the evaluation and provide future research directions. Copyright ©2016 ISCA. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_2308457X_v08-12-September-2016_n_p823_McLaren
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Evaluation Speaker recognition Speakers in the wild database Audio recordings Character recognition Database systems Speech communication Speech processing Acoustic conditions Evaluation Evaluation results Future research directions International team Speaker recognition Speaker recognition evaluations Text independents Speech recognition
spellingShingle	Evaluation Speaker recognition Speakers in the wild database Audio recordings Character recognition Database systems Speech communication Speech processing Acoustic conditions Evaluation Evaluation results Future research directions International team Speaker recognition Speaker recognition evaluations Text independents Speech recognition McLaren, M. Ferrer, L. Castan, D. Lawson, A. Morgan N. Georgiou P. Morgan N. Narayanan S. Metze F. Amazon Alexa; Apple; eBay; et al.; Google; Microsoft The 2016 speakers in thewild speaker recognition evaluation
topic_facet	Evaluation Speaker recognition Speakers in the wild database Audio recordings Character recognition Database systems Speech communication Speech processing Acoustic conditions Evaluation Evaluation results Future research directions International team Speaker recognition Speaker recognition evaluations Text independents Speech recognition
description	The newly collected Speakers in the Wild (SITW) database was central to a text-independent speaker recognition challenge held as part of a special session at Interspeech 2016. The SITW database is composed of audio recordings from 299 speakers collected from open source media, with an average of 8 sessions per speaker. The recordings contain unconstrained or "wild" acoustic conditions, rarely found in large speaker recognition datasets, and multi-speaker recordings for both speaker enrollment and verification. This article provides details of the SITW speaker recognition challenge and analysis of evaluation results. There were 25 international teams involved in the challenge of which 11 teams participated in an evaluation track. Teams were tasked with applying existing and novel speaker recognition algorithms to the challenges associated with the real world conditions of SITW. We provide an analysis of some of the top performing systems submitted during the evaluation and provide future research directions. Copyright ©2016 ISCA.
format	CONF
author	McLaren, M. Ferrer, L. Castan, D. Lawson, A. Morgan N. Georgiou P. Morgan N. Narayanan S. Metze F. Amazon Alexa; Apple; eBay; et al.; Google; Microsoft
author_facet	McLaren, M. Ferrer, L. Castan, D. Lawson, A. Morgan N. Georgiou P. Morgan N. Narayanan S. Metze F. Amazon Alexa; Apple; eBay; et al.; Google; Microsoft
author_sort	McLaren, M.
title	The 2016 speakers in thewild speaker recognition evaluation
title_short	The 2016 speakers in thewild speaker recognition evaluation
title_full	The 2016 speakers in thewild speaker recognition evaluation
title_fullStr	The 2016 speakers in thewild speaker recognition evaluation
title_full_unstemmed	The 2016 speakers in thewild speaker recognition evaluation
title_sort	2016 speakers in thewild speaker recognition evaluation
url	http://hdl.handle.net/20.500.12110/paper_2308457X_v08-12-September-2016_n_p823_McLaren
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The 2016 speakers in thewild speaker recognition evaluation

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