Index Generation of BGM Video Based on Distinctive Comments

IR

Abstract

The purpose of this study is to generate indexes for background music (BGM) based on distinctive comments annotated to BGM videos posted on Nico Nico Videos. Our proposed method detects the end/start positions of the BGM considering the increase/decrease in the number of comments, comments distinctive to the songs, and exclamatory expressions annotated to the videos. The evaluation result indicated that the proposed method could generate correct indexes within a 10 s error for BGM videos less than 40 min long and with annotations of over 30,000 comments.

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