Voice2SQL: A Hybrid Intelligent System for the Recovery of Information from Databases by Means of Spoken Natural Language

Author

Florez-Choque, Omar U.

Author_Institution

National University of San Agustin, Peru

fYear

2006

fDate

Dec. 2006

Firstpage

673

Lastpage

676

Abstract

In this article, it is proposed a model of recovery of information from a database through queries in Natural Language using the voice as input vector. This model incorporates a Hybrid Intelligent System based on Genetic Algorithms and a Self-Organizing Map of Kohonen (SOM) to recognize the present phonemes in a word through time, which allows us to remake up a word with speaker independence. Besides, it is proposed the use of a compiler with grammar of type 2 according to the Chomsky Hierarchy to support the syntactic and semantic structure in Spanish language. Our experiments suggest that the voice and Natural Language improve notably the Human-Computer interaction regarding with traditional methods, also that it is possible to achieve a more exact recognition of words by using neural networks SOM regarding to previous approaches as Hidden Markov Models (HMM).

Keywords

Data mining; Databases; Feature extraction; Genetic algorithms; Hidden Markov models; Hybrid intelligent systems; Natural languages; Neural networks; Signal processing; Speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Hiding and Multimedia Signal Processing, 2006. IIH-MSP '06. International Conference on

Conference_Location

Pasadena, CA, USA

Print_ISBN

0-7695-2745-0

Type

conf

DOI

10.1109/IIH-MSP.2006.265091

Filename

4041811