Automatic Phonetic Labeling at Word Level Using the Dynamics of Changing Codebook Vectors

Authors

  • Sergio Suárez Guerra Instituto Politécnico Nacional, Centro de Investigación en Computación
  • José Luis Oropeza Rodríguez Instituto Politécnico Nacional, Centro de Investigación en Computación

DOI:

https://doi.org/10.13053/cys-24-2-3229

Keywords:

Phonetic labeling, voice recognition

Abstract

An alternative solution is described regarding the phonetic labeling that compose a set of pronounced by an announcer, susceptible of being used in any language, according to the needs and characteristics associated with the proposal. The procedure is based on the monitoring of the dynamics of change of the cepstral vectors associated with the frequency of Mel (MFCCs) that make up the Book Code (LC), extracted from the word to be labeled. This dynamics of change analyzes where a transition from one vector (MFCC) of the LC occurs to another, as well as the disturbances that occur in the zone of change due to the phonetic concatenation. Metrics are established to consider coarticulation noise and define the location of the phonetic separation boundary. Two methods are used to evaluate the dynamics of vector change and deliver the most accurate labeling. The percentage of recognition and correct labeling obtained with this application is 97.9% lower by 1.06%, with respect to the percentage of recognition obtained on the same corpus of words, but using manual labeling. The more important are that, the time used in the labeling of the voice corpus automatically is significantly less than the estimate of being done manually, in addition to eliminating personal subjectivity in the labeling work.

Author Biography

Sergio Suárez Guerra, Instituto Politécnico Nacional, Centro de Investigación en Computación

Profesor-investigador del CIC-IPN desde 1998, Dr. en Ciencias Técnicas de la Informática graduado en Rusia en 1979. Jefe del Laboratorio de Procesamiento Digital de Señales en el CIC-IPN

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Published

2020-06-23

Issue

Vol. 24 No. 2 (2020): Thematic Issue on Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez)

Section

Articles

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