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Explicit segmentation of speech using gaussian models
Bonafonte Cávez, Antonio; Nogueiras Rodríguez, Albino; Rodriguez-Garrido, A
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
The authors investigate an automatic method to segment labeled speech. The method needs an initial estimation of the segmentation which is provided by an alignment based on HMM. Afterwards, the boundaries are refined moving the frontier frames to the segment which is more similar to the speech frame. Gaussian PDFs are used as a similarity measure. The performance of the method is evaluated using the TIMIT database. If boundary deviations (from the reference position) larger than 20 ms are counted as errors, then the replacement of the boundaries reduces the error by 30%. Additional experiments show how the proposed method makes the performance independent of the speaker dependent or speaker independent data used to estimate the HMM.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural
Natural language processing (Computer science)
Processament en llenguatge natural (Informàtica)
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
H. TIMOTHY BRUMMELL, WILLIAM IDSARDI CITATION DELAWARE, NEW CASTLE, DELAWARE
         

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