Digital Music Recommendation Technology for Music Teaching Based on Deep Learning

Abstract

With the rapid development of music streaming media service industry, users can easily hear any song on mobile devices. Internet has become a huge music storage platform. With the development of network and large-scale digital music industry, the acquisition and listening of music are presented to users in a more convenient way. How to find the music loved by users from the massive Internet digital music data has become the key problem and main goal to be solved in the field of music information retrieval. Personalized music recommendation system can accurately find and push songs that users may be interested in from tens of millions of huge music libraries according to users’ information under the condition that users only have vague demand for listening to songs. Relying on the traditional search method to find the music that you are interested in can no longer meet the needs of users, so the current music recommendation system needs to dig out the music that has no clear needs in the long tail to help people find their favorite songs.

Music Deep Learning: Deep Learning Methods for Music Signal Processing—A Review of the State-of-the-Art

“…MIR refers to the extraction of characterizing information from music data. Such information can then be exploited for a wide range of applications, such as genre classification [15], [16], music recommendation [17], [18], music source separation [19], singing voice detection [20], instrument recognition [21], music emotion recognition [22] and transcription [23]. All of the above applications aid in the digital preservation of music, by constructing and managing song databases, as well as the study of different music genres.…”

“…The automatic generation of music content has spun discussions on whether this new way to create art will eventually replace musicians. However, the more realistic projection for the future is that MG can serve as a valuable tool to musicians and educators alike, to explore new approaches to composition and teaching [17], [24].…”

A New Audio Approach Based on User Preferences Analysis to Enhance Music Recommendations

“…For example, the work proposed in Dong et al [6] combines between audio and lyrics data to construct a recommendation system based on deep learning models. In a related study within the same field, researchers proposed a deep learning-based technique for digital music recommendation [7].…”