Corpora compilation for prosody-informed speech processing

Research on speech technologies necessitates spoken data, which is usually obtained through read recorded speech, and specifically adapted to the research needs. When the aim is to deal with the prosody involved in speech, the available data must reflect natural and conversational speech, which is u...

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Detalles Bibliográficos
Autores: Oktem, Alp, Farrús, M., Bonafonte Cávez, Antonio|||0000-0002-6240-9915
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/454245
Acceso en línea:https://hdl.handle.net/2117/454245
https://dx.doi.org/10.1007/s10579-021-09556-2
Access Level:acceso abierto
Palabra clave:Speech technologies
Spoken data
Prosody
Conversational speech
Speech corpora
Machine learning
Deep learning
Punctuation restoration
Machine translation
Parallel corpora.
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repository_id_str
spelling Corpora compilation for prosody-informed speech processingOktem, AlpFarrús, M.Bonafonte Cávez, Antonio|||0000-0002-6240-9915Speech technologiesSpoken dataProsodyConversational speechSpeech corporaMachine learningDeep learningPunctuation restorationMachine translationParallel corpora.Research on speech technologies necessitates spoken data, which is usually obtained through read recorded speech, and specifically adapted to the research needs. When the aim is to deal with the prosody involved in speech, the available data must reflect natural and conversational speech, which is usually costly and difficult to get. This paper presents a machine learning-oriented toolkit for collecting, handling, and visualization of speech data, using prosodic heuristic. We present two corpora resulting from these methodologies: PANTED corpus, containing 250 h of English speech from TED Talks, and Heroes corpus containing 8 h of parallel English and Spanish movie speech. We demonstrate their use in two deep learning-based applications: punctuation restoration and machine translation. The presented corpora are freely available to the research community.This work was largely done during the doctoral studies of the first author in Universitat Pompeu Fabra. The second author has been funded by the Agencia Estatal de Investigación (AEI), Ministerio de Ciencia, Innovación y Universidades and the Fondo Social Europeo (FSE) under Grant RYC-2015-17239 (AEI/FSE, UE).Peer Reviewed20212021-09-0420262026-02-09journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/454245https://dx.doi.org/10.1007/s10579-021-09556-2reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4542452026-05-27T15:37:01Z
dc.title.none.fl_str_mv Corpora compilation for prosody-informed speech processing
title Corpora compilation for prosody-informed speech processing
spellingShingle Corpora compilation for prosody-informed speech processing
Oktem, Alp
Speech technologies
Spoken data
Prosody
Conversational speech
Speech corpora
Machine learning
Deep learning
Punctuation restoration
Machine translation
Parallel corpora.
title_short Corpora compilation for prosody-informed speech processing
title_full Corpora compilation for prosody-informed speech processing
title_fullStr Corpora compilation for prosody-informed speech processing
title_full_unstemmed Corpora compilation for prosody-informed speech processing
title_sort Corpora compilation for prosody-informed speech processing
dc.creator.none.fl_str_mv Oktem, Alp
Farrús, M.
Bonafonte Cávez, Antonio|||0000-0002-6240-9915
author Oktem, Alp
author_facet Oktem, Alp
Farrús, M.
Bonafonte Cávez, Antonio|||0000-0002-6240-9915
author_role author
author2 Farrús, M.
Bonafonte Cávez, Antonio|||0000-0002-6240-9915
author2_role author
author
dc.subject.none.fl_str_mv Speech technologies
Spoken data
Prosody
Conversational speech
Speech corpora
Machine learning
Deep learning
Punctuation restoration
Machine translation
Parallel corpora.
topic Speech technologies
Spoken data
Prosody
Conversational speech
Speech corpora
Machine learning
Deep learning
Punctuation restoration
Machine translation
Parallel corpora.
description Research on speech technologies necessitates spoken data, which is usually obtained through read recorded speech, and specifically adapted to the research needs. When the aim is to deal with the prosody involved in speech, the available data must reflect natural and conversational speech, which is usually costly and difficult to get. This paper presents a machine learning-oriented toolkit for collecting, handling, and visualization of speech data, using prosodic heuristic. We present two corpora resulting from these methodologies: PANTED corpus, containing 250 h of English speech from TED Talks, and Heroes corpus containing 8 h of parallel English and Spanish movie speech. We demonstrate their use in two deep learning-based applications: punctuation restoration and machine translation. The presented corpora are freely available to the research community.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-09-04
2026
2026-02-09
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/454245
https://dx.doi.org/10.1007/s10579-021-09556-2
url https://hdl.handle.net/2117/454245
https://dx.doi.org/10.1007/s10579-021-09556-2
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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