View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Queen Mary Research Online HMM-BASED GLISSANDO DETECTION FOR RECORDINGS OF CHINESE BAMBOO FLUTE Changhong Wang1, Emmanouil Benetos1, Xiaojie Meng2, Elaine Chew1 1Centre for Digital Music, Queen Mary University of London, UK fchanghong.wang,emmanouil.benetos,
[email protected] 2Department of Chinese Music, China Conservatory of Music, China
[email protected] ABSTRACT Playing techniques in non-Western instruments, while sim- ilarly important, are often overlooked. Take for example, Playing techniques such as ornamentations and articula- one of the world’s most ancient instruments, the Chinese tion effects constitute important aspects of music perfor- bamboo flute (also known as the Dizi or Zhudi, thereafter mance. However, their computational analysis is still at referred to as CBF): many listeners are most often cap- an early stage due to a lack of instrument diversity, estab- tivated by its unique timbre, which belies the twenty or lished methodologies and informative data. Focusing on more playing techniques invoked when performing on the the Chinese bamboo flute, we introduce a two-stage glis- instrument. To our knowledge, only Ayers [15, 16] has sando detection system based on hidden Markov models done some analysis of CBF playing techniques through (HMMs) with Gaussian mixtures. A rule-based segmen- synthesis. This work focused only on trills, tremolos and tation process extracts glissando candidates that are con- flutter-tongue. But many other techniques remain to be ex- secutive note changes in the same direction. Glissandi are plored. For the case of other non-Western instruments, lim- then identified by two HMMs.