MUSEMBLE: A novel music retrieval system with automatic voice query transcription and reformulation

So far, many researches have been done to develop efficient music retrieval systems, and query-by-humming has been considered as one of the most intuitive and effective query methods for music retrieval. For the voice humming to be a reliable query source, elaborate signal processing and acoustic similarity measurement schemes are necessary. On the other hand, recently, there has been an increased interest in query reformulation using relevance feedback with evolutionary techniques such as genetic algorithm for multimedia information retrieval. However, these techniques have not been exploited widely in the field of music retrieval. In this paper, we develop a novel music retrieval system called MUSEMBLE (MUSic enEMBLE) based on two distinct features: (i) A sung or hummed query is automatically transcribed into a sequence of pitch and duration pairs with improved accuracy for music representation. More specifically, we developed two new and unique techniques called WAE (windowed avera...

• Type: Journal
• Year: 2008
• Where: JSS
• Authors: Seungmin Rho, Byeong-jun Han, Eenjun Hwang, Minkoo Kim
• Keywords: Genetic Algorithm, JSS 2008, Music Retrieval, Relevance Feedback