Paper Info
Title
Automatic Phonetic Labeling At Word Level Using The Dynamics Of Changing Codebook Vectors
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.
Year
DOI
Venue
2020
10.13053/CyS-24-2-3229
COMPUTACION Y SISTEMAS
Keywords
DocType
Volume
Phonetic labeling, voice recognition
Journal
24
Issue
ISSN
Citations 
2
1405-5546
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Sergio Suárez Guerra100.68
José Luis Oropeza Rodríguez256.49