JOURNAL ARTICLE

Speech data system and computer database design based on improved genetic algorithm.

  • Published In: Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.), 2023, v. 23, n. 3. P. 1691 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Zhang, Weiwei 3 of 3

Abstract

This article focuses on the application of an Improved Genetic Algorithm (IGA) to optimize the design and performance of speech database systems in intelligent computer environments. The study presents a speech system architecture based on client-server design and integrates IGA to enhance parameter optimization during Hidden Markov Model (HMM) training for speech recognition. Experimental results demonstrate that IGA achieves better convergence, lower error rates (minimum error of 0.0079), and an 8% increase in speech recognition accuracy compared to traditional genetic algorithms and other methods, with overall recognition efficiency exceeding 95%. The findings suggest that IGA effectively improves data acquisition and recognition efficiency in speech databases, though the article notes that further research is needed to advance voice system technologies more broadly.

Additional Information

  • Source:Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.). 2023/07, Vol. 23, Issue 3, p1691
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2023
  • ISSN:1472-7978
  • DOI:10.3233/JCM-226698
  • Accession Number:164364992
  • Copyright Statement:Copyright of Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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