An online noun phrase translation method based on speech recognition technology

Due to the low translation accuracy of traditional methods, a noun phrase online translation method based on speech recognition technology is proposed. Firstly, an online speech signal recogniser is used to collect the speech signals of noun phrases, and Fourier transform is used for the denoising process. Secondly, based on the denoised speech signal, a benchmark translation context is set to extract the features of noun phrase speech signals in the optimal translation context. Finally, a transformation layer is introduced into the seq2seq model, with the source noun phrase as input and the target noun phrase as output, to construct a neural machine translation model for noun phrases and complete online translation of noun phrases. The experimental results show that the method proposed in this paper can accurately recognise the speech signals of noun phrases and improve the accuracy of online translation. The accuracy of online translation remains above 93%.

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Publication Details

Journal
International Journal of Biometrics
Published
2024-08-15
DOI
https://doi.org/10.1504/ijbm.2025.10066023
Primary Topic
Advanced Computational Techniques and Applications
Type
article
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article

An online noun phrase translation method based on speech recognition technology

Kun Li
International Journal of Biometrics
Advanced Computational Techniques and Applications
article

An online noun phrase translation method based on speech recognition technology

Kun Li
article en

Abstract

Due to the low translation accuracy of traditional methods, a noun phrase online translation method based on speech recognition technology is proposed. Firstly, an online speech signal recogniser is used to collect the speech signals of noun phrases, and Fourier transform is used for the denoising process. Secondly, based on the denoised speech signal, a benchmark translation context is set to extract the features of noun phrase speech signals in the optimal translation context. Finally, a transformation layer is introduced into the seq2seq model, with the source noun phrase as input and the target noun phrase as output, to construct a neural machine translation model for noun phrases and complete online translation of noun phrases. The experimental results show that the method proposed in this paper can accurately recognise the speech signals of noun phrases and improve the accuracy of online translation. The accuracy of online translation remains above 93%.

International Journal of BiometricsVol. 1(1)
Jiaozuo University (CN)
Quality Education
Openalex Percentile: Top 89%
Advanced Computational Techniques and Applications
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An online noun phrase translation method based on speech recognition technology — Kun Li · International Journal of Biometrics (2024) | TGRS Research Map | TGRS