Towards musical query-by-semantic-description using the CAL500 data set
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A music search engine built upon audio-based and web-based similarity measures
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Using natural language input and audio analysis for a human-oriented MIR system
WEDELMUSIC'02 Proceedings of the Second international conference on Web delivering of music
Combining audio content and social context for semantic music discovery
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
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We propose a new approach to a music search engine that can be accessed via natural language queries. As with existing approaches, we try to gather as much contextual information as possible for individual pieces in a (possibly large) music collection by means of Web retrieval. While existing approaches use this textual information to construct representations of music pieces in a vector space model, in this paper, we propose a document-centered technique to retrieve music pieces relevant to arbitrary natural language queries. This technique improves the quality of the resulting document rankings substantially. We report on the current state of the research and discuss current limitations, as well as possible directions to overcome them.