Song List Recommendation based on User Music Needs

  • 沈 敬濠

Student thesis: Doctoral Thesis


Music has always been an indispensable element in people's lives and music is everywhere You can see people wearing headphones and listening to your favorite music anytime anywhere With the development of digital music users want it It is more and more convenient to obtain music and Chinese pop music is the most popular song among Chinese People often express their feelings by listening to songs There are many different situations that can be explored in Chinese music However many of them are currently Well-known music streaming companies have launched different recommended song lists such as music styles or the latest popular songs but the choices available to users are still insufficient In order to find out more about the situational theme we return to the need to listen to music propose to use the user's music needs as a starting point to create different theme songs and what type of theme will be what the user wants? We summed up the three major aspects respectively "Emotion Theme" "Scene Theme" and "Character and Personality Trait Theme" In order to establish the theme of the follow-up music song list benchmarks and effectively match the user's needs to recommend songs we built Lyrics Chatbot while recommending songs find the lyrics that match the user’s mood to attract users to make choices Through experiments we prove that in the analysis of the lyrics structure when we make song recommendations based on models that only consider chorus it is better to recommend the first song than to consider only the verse or whole lyrics
Date of Award2019
Original languageEnglish
SupervisorWen-Hsiang Lu (Supervisor)

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