Title: Intelligent recognition English translation model based on speech recognition

Authors: Xiulian Han; Yawei Ran

Addresses: Department of Foreign Language Teaching, Hebei Polytechnic Institute, Shijiazhuang, 050000, Hebei, China ' International College of Broadcasting, Hebei Institute of Communications, Shijiazhuang, 050000, Hebei, China

Abstract: This article uses the physical model sampling survey method, mapping method and parameter analogy method to collect data, analyses the practicality of speech recognition from the four aspects of the model's translation speed, efficiency, language sense and connectivity, and creates a translation model suitable for intelligent recognition. The research results found that in terms of translation speed evaluation, there were 268 samples with the same evaluation by machines and humans, with a consistency rate of 96.58% and a correlation coefficient of 0.74. In terms of language perception evaluation, the consistency rate reached 99.87% and a correlation coefficient of 0.512. In terms of translation efficiency evaluation, the consistency rate was as high as 96.87%, and the correlation coefficient was 0.554. In terms of connectivity evaluation, the consistency rate was as high as 95.19%, and the correlation coefficient was 0.614.

Keywords: speech recognition; speech signal; English translation model; translation speed.

DOI: 10.1504/IJCSYSE.2026.151338

International Journal of Computational Systems Engineering, 2026 Vol.10 No.1/2/3/4, pp.90 - 103

Received: 25 Sep 2023
Accepted: 24 Oct 2023
Published online: 26 Jan 2026 *

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