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In this paper, we discuss the use of knowledge for analyzing and retrieving music contents semantically. First, we present Context-based Music Recommendation (COMUS) ontology to reason desired user emotion state from context and user preference information in the ontology. COMUS is a music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into...
Query reformulation has been suggested as an effective way to improve retrieval efficiency in text information retrieval and one of the well-known techniques for query reformulation is user relevance feedback. Recently, there has been an increased interest in the query reformulation using relevance feedback with evolutionary techniques such as genetic algorithm for multimedia information retrieval...
In this paper, we present a scheme for efficient humming-based music retrieval. For that purpose, we first describe how to extract a sequence of pitch and duration pairs as its feature information from sung or hummed query accurately and automatically. And then, we propose a novel scheme for reformulating user query to improve retrieval performance. The scheme is based on user relevance feedback with...
In this paper, we propose a new scheme for transcribing sung or hummed queries into a sequence of pitch and duration pairs automatically for efficient music retrieval. More specifically, we present two novel methods called WAE (windowed average energy) and dynamic threshold method for ADF onsets for note segmentation and onset/offset detection in acoustic signal, respectively. The former improves...
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