CBFdataset: A Dataset of Chinese Bamboo Flute Performances
CBFdataset is a dataset of Chinese bamboo flute (CBF) performances, created for ecologically valid analysis of music playing techniques in context. The dataset contains monophonic recordings of representative CBF playing techniques and classic CBF pieces recorded and annotated by professional players.
The periodic modulation dataset, CBF-periDB, is a subset of the CBFdataset, which is specifically created for periodic modulation analysis. This dataset contains recordings of four types of isolated playing techniques–vibrato, tremolo, trill, and flutter-tongue–and twenty full-length pieces recorded by ten professional CBF players from the China Conservatory of Music. Each player performs both isolated periodic modulations and two pieces selected from Busy Delivering Harvest, Morning, Jolly Meeting, Flying Partridge. All data is recorded in a professional recording studio using a Zoom H6 recorder at 44.1kHz/24-bits.
Details of the dataset information and file organisation can be found in the CBFdataset_Readme.pdf file. Besides CBF-periDB, there are two other subsets in the CBFdataset: CBF-petsDB and CBF-piexDB, which cover other playing techniques and a large number of expanded pieces. These subsets are being prepared for public release. You can find relevant updates and demos on the CBFdataset website: http://c4dm.eecs.qmul.ac.uk/CBFdataset.html.
Any queries, please contact Changhong at email@example.com. For CBF-periDB, please cite the paper:
C. Wang, E. Benetos, V. Lostanlen, and E. Chew, "Adaptive Time–Frequency Scattering for Periodic Modulation Recognition in Music Signals," 20th International Society for Music Information Retrieval Conference (ISMIR), Delft, Nov 2019.
- Is compiled by
- Conference paper: https://qmro.qmul.ac.uk/xmlui/handle/123456789/59179 (URL)
- C. Wang, E. Benetos, V. Lostanlen, and E. Chew, "Adaptive Time–Frequency Scattering for Periodic Modulation Recognition in Music Signals," 20th International Society for Music Information Retrieval Conference (ISMIR), Delft, Nov 2019.