Bio-inspired broad-class phonetic labelling

Gómez Vilda, Pedro and Ferrández Vicente, José Manuel and Rodellar Biarge, M. Victoria and Martínez Olalla, Rafael and Muñoz, Cristina and Álvarez Marquina, Agustin and Fernández, L.M. (2008). Bio-inspired broad-class phonetic labelling. In: "1st IAPR Workshop on Cognitive Information Processing", 09/06/2008-10/06/2008, Santorini, Grecia.


Title: Bio-inspired broad-class phonetic labelling
  • Gómez Vilda, Pedro
  • Ferrández Vicente, José Manuel
  • Rodellar Biarge, M. Victoria
  • Martínez Olalla, Rafael
  • Muñoz, Cristina
  • Álvarez Marquina, Agustin
  • Fernández, L.M.
Item Type: Presentation at Congress or Conference (Article)
Event Title: 1st IAPR Workshop on Cognitive Information Processing
Event Dates: 09/06/2008-10/06/2008
Event Location: Santorini, Grecia
Title of Book: Proceedings of the 1st IAPR Workshop on Cognitive Information Processing, IAPR 2008
Date: 2008
Freetext Keywords: Adaptive Speech Processing, Phonetic Labeling, Bio-inspired Systems, Cognitive Audio.
Faculty: Facultad de Informática (UPM)
Department: Arquitectura y Tecnología de Sistemas Informáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Recent studies have shown that the correct labeling of phonetic classes may help current Automatic Speech Recognition (ASR) when combined with classical parsing automata based on Hidden Markov Models (HMM).Through the present paper a method for Phonetic Class Labeling (PCL) based on bio-inspired speech processing is described. The methodology is based in the automatic detection of formants and formant trajectories after a careful separation of the vocal and glottal components of speech and in the operation of CF (Characteristic Frequency) neurons in the cochlear nucleus and cortical complex of the human auditory apparatus. Examples of phonetic class labeling are given and the applicability of the method to Speech Processing is discussed.

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Item ID: 4667
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Deposited by: Memoria Investigacion
Deposited on: 26 Oct 2010 11:42
Last Modified: 20 Apr 2016 13:47
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