Frontiers of Data and Domputing ›› 2021, Vol. 3 ›› Issue (4): 81-92.doi: 10.11871/jfdc.issn.2096-742X.2021.04.007

• Technology and Applicaton • Previous Articles     Next Articles

A Survey on Popular Digital Audio Prediction Techniques

ZHANG Yining1,2(),HE Hongbo1,*(),WANG Runqiang1()   

  1. 1. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2021-01-21 Online:2021-08-20 Published:2021-08-30
  • Contact: HE Hongbo E-mail:zhangyining@cnic.cn;hhb@cnic.cn;wrq@cnic.cn

Abstract:

[Objective] In recent years, the number of online digital audio audiences have increased greatly. It is of great significance to study the popular digital audio prediction techniques for the development of digital audio systems. [Coverage] Relevant papers in this field are collected by using keyword search and citation retrieval. [Methods] Through extensive literature review, we have summarized the definitions of popular indicators by scholars in this research field, categorized the four main types of internal features commonly used for predicting popular audio, reviewed and analyzed commonly used prediction models. We also forecast the future development trends and research directions of this field. [Results] By selecting appropriate feature representations, popular music and popular podcasts can be successfully predicted, in which the research on popular music prediction are more versatile and impressive. [Limitations] There is little domestic research in the field of popular audio prediction, so the number of retrieved Chinese literature is very small. [Conclusions] There is still huge growth potential in popular digital audio prediction, especially for podcast prediction, which is still an underdeveloped realm in China.

Key words: digital audio, music, podcast, popularity prediction, audio features, machine learning, deep learning