Research on Audio Retrieval Methods Based on Natural Language Processing

Shuqing Zhang, Wenyi Zhu, Xiaoya He and Nannan Zhou
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Shuqing Zhang: School of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao, China
Wenyi Zhu: School of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao, China
Xiaoya He: Malvern College Qingdao, Qingdao, China
Nannan Zhou: School of Economics and Management, Qingdao University of Science and Technology, Qingdao, China

Journal of Economic Statistics, 2025, vol. 3, issue 1, 32-44

Abstract: With the continuous improvement of social informatization level, multimedia network has become an indispensable part of people's work and life. The demand for massive multimedia data processing and transmission technology is also more and more urgent, so that audio retrieval technology has become a research hotspot. Audio technology is an important part of multimedia data processing, and the form is complex and diverse. Audio processing technology plays a key role in multimedia data processing, and its manifestations are very different. How to accurately extract and analyze diverse audio data has become a hot topic in today's society. This paper discusses the techniques required for audio content extraction and the process of research and analysis, and outlines the latest progress of audio research at home and abroad. Next, a comprehensive introduction to the characteristics of audio analysis is given, and some of the features are extracted using different methods. On this basis, an audio retrieval model based on natural language processing is constructed by combining the structure, methods and models of natural language processing, trained and numerically simulated, and the results show that it is feasible to use natural language processing for audio retrieval.

Keywords: Audio Retrieval; Natural Language Processing; Fast Fourier Transform; Hidden Markov Model (search for similar items in EconPapers)
Date: 2025
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