Background Speech Synchronous Recognition Method of E-commerce Platform Based on Hidden Markov Model

Authors: Pei Jiang, Dongchen Wang

Abstract: In order to improve the effect of e-commerce platform background speech synchronous recognition and solve the problem that traditional methods are vulnerable to sudden noise, resulting in poor recognition effect, this paper proposes a background speech synchronous recognition method based on Hidden Markov model. Combined with the principle of speech recognition, the speech feature is collected. Hidden Markov model is used to input and recognize high fidelity speech filter to ensure the effectiveness of signal processing results. Through the de-noising of e-commerce platform background voice, and the language signal cache and storage recognition, using vector graph buffer audio, through the Ethernet interface transplant related speech recognition sequence, thus realizing background speech synchronization, so as to realize the language recognition, improve the recognition accuracy. Finally, the experimental results show that the background speech synchronous recognition method based on Hidden Markov model is better than the traditional methods.

Pages: 344-351

DOI: 10.46300/9106.2022.16.42

International Journal of Circuits, Systems and Signal Processing, E-ISSN: 1998-4464, Volume 16, 2022, Art. #42