Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/41609
Type of publication: research article
Type of publication (PDB): Straipsnis Clarivate Analytics Web of Science / Article in Clarivate Analytics Web of Science (S1)
Field of Science: Informatika / Informatics (N009)
Author(s): Šilingas, Darius;Telksnys, Adolfas Laimutis
Title: Specifics of hidden Markov Model modifications for large vocabulary continuous speech recognition
Is part of: Informatica: international journal. Vilnius : Institute of mathematics and informatics, 2004, Vol. 15, no. 1
Extent: p. 93-110
Date: 2004
Keywords: Large vocabulary continuous speech recognition;Hidden Markov model;Viterbi recognition;Beam search;Context-dependent phones;Gaussian mixture;Llanguage modeling;HTK;WSJCAM0
Abstract: Specifics of hidden Markov model-based speech recognition are investigated. Influence of modeling simple and context-dependent phones, using simple Gaussian, two and three-component Gaussian mixture probability density functions for modeling feature distribution, and incorporating language model are discussed. Word recognition rates and model complexity criteria are used for evaluating suitability of these modifications for practical applications. Development of large vocabulary continuous speech recognition system using HTK toolkit and WSJCAM0 English speech corpus is described. Results of experimental investigations are presented
Internet: https://www.mii.lt/informatica/pdf/INFO540.pdf
Affiliation(s): Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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