Dynamic time warping applied to detection of confusable word pairs in automatic speech recognition

In this paper we present a rnethod to predict if two words are likely to be confused by an Autornatic SpeechRecognition (ASR) systern. This method is based on the c1assical Dynamic Time Warping (DTW) technique. This technique, which is usually used in ASR to measure the distance between two speech s...

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Detalles Bibliográficos
Autores: Anguita Ortega, Jan, Hernando Pericás, Francisco Javier|||0000-0002-1730-8154
Tipo de recurso: artículo
Fecha de publicación:2005
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:2099/10099
Acceso en línea:https://hdl.handle.net/2099/10099
Access Level:acceso abierto
Palabra clave:Telecommunication
Telecomunicació -- Revistes
Reconeixement automàtic de la parla
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic
Descripción
Sumario:In this paper we present a rnethod to predict if two words are likely to be confused by an Autornatic SpeechRecognition (ASR) systern. This method is based on the c1assical Dynamic Time Warping (DTW) technique. This technique, which is usually used in ASR to measure the distance between two speech signals, is usedhere to calculate the distance between two words. With this distance the words are c1assified as confusable or not confusable using a threshold. We have tested the methodin ac1assicalfalse acceptance/false rejection framework and the Equal Error Rate (EER) was measured to be less than 3%.