Title: Speech recognition method of English translation robot based on HMM algorithm

Authors: Xiaolin Zhang; Tao Wang; Ling Jiang

Addresses: Teacher and Teaching Developing Center, Dalian Ocean University, Dalian, 116023, China ' Dalian Ocean University, Dalian, 116023, China ' Dalian Hi-Think Computer Technology Corp., Dalian, 116028, China

Abstract: To solve the problems of poor speech feature extraction and high false recognition rate in English translation robot speech recognition, a speech recognition method for English translation robot based on HMM algorithm is proposed. Firstly, the speech signal is collected and processed by noise reduction, reverberation removal, speech segmentation, volume normalisation and speech feature extraction. Then, HMM algorithm is introduced to extract the optimal speech features. Finally, the speech recognition function is constructed, and the speech features are regarded as discrepancy, and the recognition function is optimised through the error term to realise the speech recognition of the English translation robot. The experimental results show that this method can effectively extract the voice features of voice command signals. The average error rate is 1.5%, and the average recognition rate is 98.47%. The identification results of valid information and invalid information obtained are consistent with the actual results.

Keywords: HMM algorithm; English translation robot; speech recognition; noise reduction; de-reverberation; speech segmentation; volume normalisation; speech feature extraction.

DOI: 10.1504/IJRIS.2025.149718

International Journal of Reasoning-based Intelligent Systems, 2025 Vol.17 No.6, pp.397 - 405

Received: 15 Jun 2023
Accepted: 09 Aug 2023
Published online: 11 Nov 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article