In this paper, we present MusPy, an open source Python library for symbolic music generation. MusPy provides easy-to-use tools for essential components in a music generation system, including dataset management, data I/O, data preprocessing and model evaluation. In order to showcase its potential, we present statistical analysis of the eleven datasets currently supported by MusPy. Moreover, we conduct a cross-dataset generalizability experiment by training an autoregressive model on each dataset and measuring held-out likelihood on the others---a process which is made easier by MusPy's dataset management system. The results provide a map of domain overlap between various commonly used datasets and show that some datasets contain more representative cross-genre samples than others. Along with the dataset analysis, these results might serve as a guide for choosing datasets in future research. Source code and documentation are available at https://github.com/salu133445/muspy .
EPFL（洛桑联邦理工学院）；University of Edinburgh（爱丁堡大学）；Kyoto University（京都大学）
In this paper, we introduce the MIDI Degradation Toolkit (MDTK), containing functions which take as input a musical excerpt (a set of notes with pitch, onset time, and duration), and return a "degraded" version of that excerpt with some error (or errors) introduced. Using the toolkit, we create the Altered and Corrupted MIDI Excerpts dataset version 1.0 (ACME v1.0), and propose four tasks of increasing difficulty to detect, classify, locate, and correct the degradations. We hypothesize that models trained for these tasks can be useful in (for example) improving automatic music transcription pe…
VERSA: A Versatile Evaluation Toolkit for Speech, Audio, and Music
Carnegie Mellon University（卡内基梅隆大学）；Microsoft（微软公司）；Indiana University（印第安纳大学）；Nanyang Technological University（南洋理工大学）；University of Rochester（罗切斯特大学）；Renmin University of China（中国人民大学）；Shanghai Jiaotong University（上海交通大学）；Sony AI（索尼人工智能）
Carnegie Mellon University（卡内基梅隆大学）；Renmin University of China（中国人民大学）；The University of Hong Kong（香港大学）；Human Dataware Lab. Co., Ltd.（人类数据仓库实验室有限公司）；Nagoya University（名古屋大学）；Tsinghua University（清华大学）；University of California, Berkeley（加州大学伯克利分校）
This paper introduces a new open-source platform named Muskits for end-to-end music processing, which mainly focuses on end-to-end singing voice synthesis (E2E-SVS). Muskits supports state-of-the-art SVS models, including RNN SVS, transformer SVS, and XiaoiceSing. The design of Muskits follows the style of widely-used speech processing toolkits, ESPnet and Kaldi, for data prepossessing, training, and recipe pipelines. To the best of our knowledge, this toolkit is the first platform that allows a fair and highly-reproducible comparison between several published works in SVS. In addition, we als…
Academia Sinica（中央研究院）；Institute of Information Science, Academia Sinica（中央研究院信息科学研究所）
We present and release Omnizart, a new Python library that provides a streamlined solution to automatic music transcription (AMT). Omnizart encompasses modules that construct the life-cycle of deep learning-based AMT, and is designed for ease of use with a compact command-line interface. To the best of our knowledge, Omnizart is the first transcription toolkit which offers models covering a wide class of instruments ranging from solo, instrument ensembles, percussion instruments to vocal, as well as models for chord recognition and beat/downbeat tracking, two music information retrieval (MIR) …
Communication University of China（中国传媒大学）；Mcgill University（麦吉尔大学）
While guitar tablature has become a popular topic in MIR research, there exists no such a guitar tablature dataset that focuses on the soundtracks of anime and video games, which have a surprisingly broad and growing audience among the youths. In this paper, we present AnimeTAB, a fingerstyle guitar tablature dataset in MusicXML format, which provides more high-quality guitar tablature for both researchers and guitar players. AnimeTAB contains 412 full tracks and 547 clips, the latter are annotated with musical structures (intro, verse, chorus, and bridge). An accompanying analysis toolkit, TA…
Muskits-ESPnet: A Comprehensive Toolkit for Singing Voice Synthesis in New Paradigm
Renmin University of China（中国人民大学）；Carnegie Mellon University（卡内基梅隆大学）；Georgia Institute of Technology（佐治亚理工学院）；Duke Kunshan University（昆山杜克大学）；Cornell University（康奈尔大学）
MARBLE: Music Audio Representation Benchmark for Universal Evaluation
Multimodal Art Projection Research Community（多模态艺术投影研究社区）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）；Carnegie Mellon University（卡内基梅隆大学）；Queen Mary University of London（伦敦玛丽女王大学）；University of Manchester（曼彻斯特大学）；University of Sheffield（谢菲尔德大学）；University of Waterloo（滑铁卢大学）；University of Michigan Ann Arbor（密歇根大学安娜堡分校）；Beihang University（北京航空航天大学）；Hong Kong University of Science and Technology（香港科技大学）；Peking University（北京大学）
