In many cultures of the world, traditional percussion music/nuses mnemonic syllables that are representative of the timbres/nof instruments. These syllables are orally transmitted/nand often provide a language for percussion in those music/ncultures. Percussion patterns in these cultures thus have/na well defined representation in the form of these syllables,/nwhich can be utilized in several computational percussion/npattern analysis tasks. We explore a connected word/nspeech recognition based framework that can effectively/nutilize the syllabic representation for automatic transcription/nand recognition of audio percussion patterns. In particular,/nwe consider the case of Beijing opera and present/na syllable level hidden markov model (HMM) based system/nfor transcription and classification of percussion patterns./nThe encouraging classification results on a representative/ndataset of Beijing opera percussion patterns supports/nour approach and provides further insights on the utility of/nthese syllables for computational description of percussion/npatterns.

This work is partly supported by the European Research/nCouncil under the European Union’s Seventh Framework/nProgram, as a part of the CompMusic project (ERC grant/nagreement 267583)