Pipaset preview: A multimodal dataset for AMT and EA tasks dedicated to Chinese music instrument Pipa

Yuancheng Wang, Yuyang Jing , Wei Wei, Dorian Cazau, Olivier Adam, Qiao Wang Accompanying Website here. If you make use of PipaSet for academic purposes, please cite the following publication: PipaSet and TEAS: A Multimodal Dataset and Annotation Platform for Automatic Music Transcription and Expressive Analysis dedicated to Chinese Traditional Plucked String Instrument Pipa. IEEE ACCESS 2022. This project was led by Yuancheng Wang at Information School of Information Science and Engineering, Southeast University, China, along with my supervisor Prof. Qiao Wang from same school and Dr. Yuyang Jing from Nanjing University of the Arts, Wei Wei form Xiaozhuang University, Dr. Dorian Cazau from Institute of Mines-Télécom Atlantique in Brest France, Prof. Olivier Adam from Sorbonne University. We present PipaSet, a dataset that provides multimodal pipa recordings alongside a high diversity of annotations for Automatic Music Transcription and Expressive Analysis tasks, including note, pitch contours, string and fret positions, and playing techniques. More information will be coming soon to cover more pieces of music played by pipa.王远成、景阳阳、魏伟、多里安·卡佐（Dorian Cazau）、奥利维耶·亚当（Olivier Adam）、王桥。配套网站请见此处。若将PipaSet用于学术研究，请引用以下文献：《PipaSet与TEAS：面向中国传统弹拨乐器琵琶的自动音乐记谱（Automatic Music Transcription）与表现力分析多模态数据集及标注平台》，发表于IEEE ACCESS 2022年。本项目由中国东南大学信息科学与工程学院的王远成牵头，联合同校的王桥教授、南京艺术学院的景阳阳博士、晓庄学院的魏伟、法国布雷斯特矿业-电信大西洋研究所的多里安·卡佐博士，以及索邦大学的奥利维耶·亚当教授共同参与完成。本团队推出PipaSet数据集，该数据集包含多模态琵琶录音，以及面向自动音乐记谱与表现力分析任务的多样化标注，涵盖音符、音高轮廓、弦位与品位信息，以及演奏技法标注。后续将更新更多琵琶演奏曲目相关的数据集内容。