Automated definition of phonetically homogeneous sections of words in a natural language based on multiparameter optimization

An approach to the automated splitting of words into phonetically homogeneous parts is proposed under which the boundaries of the parts are defined as a result of solving a multiparameter optimization problem. The approach is assumed to ensure the maximum difference in the phonetic material between...

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Bibliographic Details
Published in:Journal of computer & systems sciences international Vol. 55; no. 4; pp. 609 - 618
Main Authors: Korsun, O. N., Poliev, A. V.
Format: Journal Article
Language:English
Published: Moscow Pleiades Publishing 01.07.2016
Springer Nature B.V
Subjects:
Algorithms
Analysis
Automation
Boundaries
Computer science
Control
Conversion
Engineering
Fourier transforms
Language
Mathematical models
Mathematical problems
Mechatronics
Natural language
Optimization
Pattern Recognition and Image Processing
Phonetics
Recording
Robotics
Similarity
Sound
Studies
ISSN:1064-2307, 1555-6530
Online Access:Get full text
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Summary:An approach to the automated splitting of words into phonetically homogeneous parts is proposed under which the boundaries of the parts are defined as a result of solving a multiparameter optimization problem. The approach is assumed to ensure the maximum difference in the phonetic material between the adjacent parts and the maximum similarity within the parts. The accepted measure of similarity and difference is based on the correlation between the columns of the parametric portrait matrix of the word generated as a result of a time-spectral conversion of an audio recording of the word. To obtain a numerical solution of the problem, an algorithm is proposed which is a modification of a dynamic programming technique. The experimental results are presented with several words from the Russian language taken as examples to confirm the legitimacy of the assumptions made and viability of the algorithms proposed.
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ISSN:1064-2307
1555-6530
DOI:10.1134/S1064230716040080