{"id":8770,"date":"1995-01-01T00:00:00","date_gmt":"1995-01-01T00:00:00","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/1995\/01\/01\/modelado-acustico-y-teorias-de-adaptacion-maximo-a-posteriori-map-para-reconocimiento-de-habla-continua-en-castellano\/"},"modified":"1995-01-01T00:00:00","modified_gmt":"1995-01-01T00:00:00","slug":"modelado-acustico-y-teorias-de-adaptacion-maximo-a-posteriori-map-para-reconocimiento-de-habla-continua-en-castellano","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/ciencias-tecnologicas\/modelado-acustico-y-teorias-de-adaptacion-maximo-a-posteriori-map-para-reconocimiento-de-habla-continua-en-castellano\/","title":{"rendered":"Modelado acustico y teorias de adaptacion maximo a posteriori (map) para reconocimiento de habla continua en castellano."},"content":{"rendered":"<h2>Tesis doctoral de <strong>  Alvarez Cercadillo Jos\u00e9 Jorge <\/strong><\/h2>\n<p>Se explica como se ha desarrollado un reconocedor de habla continua en castellano que dispone de mecanismos de mejora de prestaciones utilizando unidades dependientes del contexto y ajuste del sistema al locutor. Este ajuste se discute con el uso de dos metodos. El de maxima verosimilitud y el de maximo a posteriori (map) que necesita menor cantidad de datos de entrenamiento. Se desarrolla un algoritmo de entrenamiento bayesiano basado en el criterio map entrenandose con el unidades adaptadas al contexto y unidades adaptadas al locutor, concluyendo un mejor funcionamiento del reconocedor cuando se dispone de una base de datos reducida, ademas de incluir la posibilidad de incorporar nuevos datos de entrenamiento de manera incremental.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Modelado acustico y teorias de adaptacion maximo a posteriori (map) para reconocimiento de habla continua en castellano.<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Modelado acustico y teorias de adaptacion maximo a posteriori (map) para reconocimiento de habla continua en castellano. <\/li>\n<li><strong>Autor:<\/strong>\u00a0  Alvarez Cercadillo Jos\u00e9 Jorge <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Polit\u00e9cnica de Madrid<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 01\/01\/1995<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Luis Alfonso Hernandez Gomez<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: Mar\u00eda no Garcia Otero <\/li>\n<li>Carmen Garc\u00eda Mateo (vocal)<\/li>\n<li>Eduardo Lleida Solano (vocal)<\/li>\n<li>Antonio  Jos\u00e9 Rubio Ayuso (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Alvarez Cercadillo Jos\u00e9 Jorge Se explica como se ha desarrollado un reconocedor de habla continua en castellano [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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