
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>HuQin is a family of traditional Chinese bowed string instruments. Playing techniques(PTs) embodied in various playing styles add abundant emotional coloring and aesthetic feelings to HuQin performance. The complex applied techniques make HuQin music a challenging source for fundamental MIR tasks such as pitch analysis, transcription and score-audio alignment. In this paper, we present a multimodal performance dataset of HuQin music that contains audio-visual recordings of 11,992 single PT clips and 57 annotated musical pieces of classical excerpts. We systematically describe the HuQin PT taxonomy based on musicological theory and practical use cases. Then we introduce the dataset creation methodology and highlight the annotation principles featuring PTs. We analyze the statistics in different aspects to demonstrate the variety of PTs played in HuQin subcategories and perform preliminary experiments to show the potential applications of the dataset in various MIR tasks and cross-cultural music studies. Finally, we propose future work to be extended on the dataset.
15 pages, 11 figures
FOS: Computer and information sciences, Sound (cs.SD), chinese bowed string instruments, playing technique, music transcription, Information technology, performance dataset, T58.5-58.64, Computer Science - Sound, Multimedia (cs.MM), annotation, Audio and Speech Processing (eess.AS), chinese fiddle, FOS: Electrical engineering, electronic engineering, information engineering, M1-5000, Music, Computer Science - Multimedia, Electrical Engineering and Systems Science - Audio and Speech Processing
FOS: Computer and information sciences, Sound (cs.SD), chinese bowed string instruments, playing technique, music transcription, Information technology, performance dataset, T58.5-58.64, Computer Science - Sound, Multimedia (cs.MM), annotation, Audio and Speech Processing (eess.AS), chinese fiddle, FOS: Electrical engineering, electronic engineering, information engineering, M1-5000, Music, Computer Science - Multimedia, Electrical Engineering and Systems Science - Audio and Speech Processing
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
