Broad phonetic class definition driven by phone confusions

Detalhes bibliográficos
Autor(a) principal: Lopes, Carla
Data de Publicação: 2012
Outros Autores: Perdigão, Fernando
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/102726
https://doi.org/10.1186/1687-6180-2012-158
Resumo: Intermediate representations between the speech signal and phones may be used to improve discrimination among phones that are often confused. These representations are usually found according to broad phonetic classes, which are defined by a phonetician. This article proposes an alternative data-driven method to generate these classes. Phone confusion information from the analysis of the output of a phone recognition system is used to find clusters at high risk of mutual confusion. A metric is defined to compute the distance between phones. The results, using TIMIT data, show that the proposed confusion-driven phone clustering method is an attractive alternative to the approaches based on human knowledge. A hierarchical classification structure to improve phone recognition is also proposed using a discriminative weight training method. Experiments show improvements in phone recognition on the TIMIT database compared to a baseline system.
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spelling Broad phonetic class definition driven by phone confusionsConfusion MatrixConditional Random FieldFrame Error RateDiscriminative TrainingContext WindowIntermediate representations between the speech signal and phones may be used to improve discrimination among phones that are often confused. These representations are usually found according to broad phonetic classes, which are defined by a phonetician. This article proposes an alternative data-driven method to generate these classes. Phone confusion information from the analysis of the output of a phone recognition system is used to find clusters at high risk of mutual confusion. A metric is defined to compute the distance between phones. The results, using TIMIT data, show that the proposed confusion-driven phone clustering method is an attractive alternative to the approaches based on human knowledge. A hierarchical classification structure to improve phone recognition is also proposed using a discriminative weight training method. Experiments show improvements in phone recognition on the TIMIT database compared to a baseline system.2012info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/102726http://hdl.handle.net/10316/102726https://doi.org/10.1186/1687-6180-2012-158eng1687-6180Lopes, CarlaPerdigão, Fernandoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-10-10T20:31:39Zoai:estudogeral.uc.pt:10316/102726Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:19:39.668796Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Broad phonetic class definition driven by phone confusions
title Broad phonetic class definition driven by phone confusions
spellingShingle Broad phonetic class definition driven by phone confusions
Lopes, Carla
Confusion Matrix
Conditional Random Field
Frame Error Rate
Discriminative Training
Context Window
title_short Broad phonetic class definition driven by phone confusions
title_full Broad phonetic class definition driven by phone confusions
title_fullStr Broad phonetic class definition driven by phone confusions
title_full_unstemmed Broad phonetic class definition driven by phone confusions
title_sort Broad phonetic class definition driven by phone confusions
author Lopes, Carla
author_facet Lopes, Carla
Perdigão, Fernando
author_role author
author2 Perdigão, Fernando
author2_role author
dc.contributor.author.fl_str_mv Lopes, Carla
Perdigão, Fernando
dc.subject.por.fl_str_mv Confusion Matrix
Conditional Random Field
Frame Error Rate
Discriminative Training
Context Window
topic Confusion Matrix
Conditional Random Field
Frame Error Rate
Discriminative Training
Context Window
description Intermediate representations between the speech signal and phones may be used to improve discrimination among phones that are often confused. These representations are usually found according to broad phonetic classes, which are defined by a phonetician. This article proposes an alternative data-driven method to generate these classes. Phone confusion information from the analysis of the output of a phone recognition system is used to find clusters at high risk of mutual confusion. A metric is defined to compute the distance between phones. The results, using TIMIT data, show that the proposed confusion-driven phone clustering method is an attractive alternative to the approaches based on human knowledge. A hierarchical classification structure to improve phone recognition is also proposed using a discriminative weight training method. Experiments show improvements in phone recognition on the TIMIT database compared to a baseline system.
publishDate 2012
dc.date.none.fl_str_mv 2012
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/102726
http://hdl.handle.net/10316/102726
https://doi.org/10.1186/1687-6180-2012-158
url http://hdl.handle.net/10316/102726
https://doi.org/10.1186/1687-6180-2012-158
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