The EASR corpora of European Portuguese, French, hungarian and polish elderly speech

dc.contributor.authorHämäläinen, A.
dc.contributor.authorAvelar, J.
dc.contributor.authorRodrigues, S.
dc.contributor.authorDias, J.
dc.contributor.authorKolesinski, A.
dc.contributor.authorFegyó, T.
dc.contributor.authorNémeth, G.
dc.contributor.authorCsobánka, P.
dc.contributor.authorTing, K. L. H.
dc.contributor.authorHewson, D.
dc.contributor.editorNicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
dc.date.accessioned2022-05-25T12:43:10Z
dc.date.available2022-05-25T12:43:10Z
dc.date.issued2014
dc.date.updated2023-07-03T11:05:45Z
dc.description.abstractCurrently available speech recognisers do not usually work well with elderly speech. This is because several characteristics of speech (e.g. fundamental frequency, jitter, shimmer and harmonic noise ratio) change with age and because the acoustic models used by speech recognisers are typically trained with speech collected from younger adults only. To develop speech-driven applications capable of successfully recognising elderly speech, this type of speech data is needed for training acoustic models from scratch or for adapting acoustic models trained with younger adults’ speech. However, the availability of suitable elderly speech corpora is still very limited. This paper describes an ongoing project to design, collect, transcribe and annotate large elderly speech corpora for four European languages: Portuguese, French, Hungarian and Polish. The Portuguese, French and Polish corpora contain read speech only, whereas the Hungarian corpus also contains spontaneous command and control type of speech. Depending on the language in question, the corpora contain 76 to 205 hours of speech collected from 328 to 986 speakers aged 60 and over. The final corpora will come with manually verified orthographic transcriptions, as well as annotations for filled pauses, noises and damaged words.eng
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.event.date2014
dc.event.locationReykjavikeng
dc.event.title9th International Conference on Language Resources and Evaluation, LREC 2014
dc.event.typeConferênciapt
dc.identifier.citationHämäläinen, A., Avelar, J., Rodrigues, S., Dias, J., Kolesinski, A., Fegyó, T., Németh, G., Csobánka, P., Ting, K. L. H., & Hewson, D. (2014). The EASR corpora of European Portuguese, French, hungarian and polish elderly speech. Em N. Calzolari, K. Choukri, T. Declerck, H. Loftsson, B. Maegaard, J. Mariani, A. Moreno, J. Odijk, & S. Piperidis (Eds.), Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014) (pp. 1458-1464). European Language Resources Association (ELRA)
dc.identifier.isbn978-2-9517408-8-4
dc.identifier.urihttp://hdl.handle.net/10071/25544
dc.journalProceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014)
dc.language.isoeng
dc.pagination1458 - 1464
dc.peerreviewedyes
dc.publisherEuropean Language Resources Association (ELRA)
dc.relationAAL2009-2-068
dc.relation.ispartofProceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014)
dc.rightsopen access
dc.subjectAutomatic speech recognitioneng
dc.subjectCorpuseng
dc.subjectElderly speecheng
dc.subject.fosDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informaçãopor
dc.subject.fosDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
dc.subject.fosDomínio/Área Científica::Humanidades::Línguas e Literaturaspor
dc.titleThe EASR corpora of European Portuguese, French, hungarian and polish elderly speecheng
dc.typeconferenceObject
degois.publication.firstPage1458
degois.publication.lastPage1464
degois.publication.locationReykjavikeng
degois.publication.titleThe EASR Corpora of European Portuguese, French, Hungarian and Polish elderly speecheng
dspace.entity.typePublicationen
iscte.alternateIdentifiers.scopus2-s2.0-84977583701
iscte.alternateIdentifiers.wosWOS:000355611003011
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-96270
iscte.subject.odsIndústria, inovação e infraestruturaspor
iscte.subject.odsReduzir as desigualdadespor

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