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dc.contributor.authorHernando Pericás, Francisco Javier
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2016-07-21T08:55:46Z
dc.date.available2016-07-21T08:55:46Z
dc.date.issued1995
dc.identifier.citationHernando, J. Discriminative weighting of dynamic feautres in continuous-density hidden Markov models for word recognition. A: Spanish Symposium on Pattern recognition and Image Analysis. "VI Spanish Symposium on Pattern Recognition and Image Anlalysis: Córdoba: 3-7 April 1995". Córdoba: 1995, p. 293-300.
dc.identifier.urihttp://hdl.handle.net/2117/89009
dc.description.abstractSpeech dynamic features, which provide smoothed estimates of the derivatives of the spectral parameter trajectories in the current frame, are routinely used in current speech recognition systems in combination with short-term (static) spectral features. The aim of this paper is to propose a method to automatically estimate the optimum ponderation of static and dynamic features in a speech recognition system. The recognition system considered in this paper is based on Continuous-Density Hidden Markov Modelling (CDHMM), widely used in speech recognition. Our approach consists basically in 1) adding two new parameters for each state of each model that weight both kinds of speech features, and 2) estimating those parameters by means of a discriminative training algorithm that minimizes the recognition error using the recently proposed Generalized Probabilistic Descent (GPO) method. Experimental results in speaker independent digit recognition show an important increase of recognition accuracy.
dc.format.extent8 p.
dc.language.isoeng
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic
dc.subject.lcshSpeech processing systems
dc.titleDiscriminative weighting of dynamic feautres in continuous-density hidden Markov models for word recognition
dc.typeConference report
dc.subject.lemacProcessament de la parla
dc.contributor.groupUniversitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
drac.iddocument18769986
dc.description.versionPostprint (published version)
upcommons.citation.authorHernando, J.
upcommons.citation.contributorSpanish Symposium on Pattern recognition and Image Analysis
upcommons.citation.pubplaceCórdoba
upcommons.citation.publishedtrue
upcommons.citation.publicationNameVI Spanish Symposium on Pattern Recognition and Image Anlalysis: Córdoba: 3-7 April 1995
upcommons.citation.startingPage293
upcommons.citation.endingPage300


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