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Article type: Research Article
Authors: Zhang, Weiwei
Affiliations: Department of Information Engineering, Anhui Finance and Trade Vocational College, Hefei, Anhui 230601, China | E-mail: [email protected]
Correspondence: [*] Corresponding author: Department of Information Engineering, Anhui Finance and Trade Vocational College, Hefei, Anhui 230601, China. E-mail: [email protected].
Abstract: In the intelligent age, computers are required to help people complete simple daily work. Among them, computer voice databases and systems occupy a very important position in the field due to their wide application. In order to optimize the system design method, the application of IGA algorithm is proposed, and the performance of the model under the algorithm is compared and tested. The algorithm experiment shows that when the IGA objective function value is 34.4, there is no change, and the number of iterations is 100; Compared with the traditional genetic algorithm, the value of the optimal solution is always the minimum. Then the error of the optimal solution under different algorithms is compared and analyzed. It is found that the error of the optimal solution under IGA operation has the minimum value of 0.0079; The experiment of speech recognition efficiency shows that the speech recognition rate under the intervention of IGA algorithm has increased by 8%, and the overall efficiency is higher than 95%. It can be seen from the above results that IGA is helpful to the acquisition of voice database data, and improves the recognition efficiency. The feasibility of the method is high, which is of great significance to the development of China’s intelligent system industry. But at present, the overall progress of the voice system is still limited, so expanding research methods to apply to the field of voice system is still the next research direction that can be explored.
Keywords: Improved genetic algorithm, speech data system, computer database, speech recognition rate
DOI: 10.3233/JCM-226698
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1691-1703, 2023
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