An Onomatopoeia-Based Web Music Video Searching System and Its Performance Evaluation

In recent years, as use of the Internet became widespread, numerous music videos became available on Web. In Japan, many of these music videos are the CGM (Consumer Generated Media) that are created using a singing synthesis software called Hatsune Miku, and published on YouTube and other similar Web sites. Existing Web sites, however, support only the search methods based on music video title and artist name, which could not be effectively used to search for the unknown music videos such as the CGM ones. This paper presents a system model for effectively searching for the unknown music videos, which is characterized by the use of the onomatopoeia. The system model consists of a music video collecting engine for collecting pairs of music video URL and its tags, an onomatopoeia assigning engine for assigning onomatopoeias to music videos, and an onomatopoeia retriever for presenting users the music video URLs satisfying their onomatopoeia requirements. We have implemented a prototype system of the proposed system model and conducted experiments to study its performance. It has been found that with the proposed system model, a precision ratio of 66.82%, a recall ratio of 56.36%, and an F-measure of 61.14% could be achieved.