IRMAS: a dataset for instrument recognition in musical audio signals

This dataset includes musical audio excerpts with annotations of the predominant instrument(s) present. It was used for the evaluation in the following article: Bosch, J. J., Janer, J., Fuhrmann, F., & Herrera, P. “A Comparison of Sound Segregation Techniques for Predominant Instrument Recognition in Musical Audio Signals”, in Proc. ISMIR (pp. 559-564), 2012 Please Acknowledge IRMAS in Academic Research IRMAS is intended to be used for training and testing methods for the automatic recognition of predominant instruments in musical audio. The instruments considered are: cello, clarinet, flute, acoustic guitar, electric guitar, organ, piano, saxophone, trumpet, violin, and human singing voice. This dataset is derived from the one compiled by Ferdinand Fuhrmann in his PhD thesis, with the difference that we provide audio data in stereo format, the annotations in the testing dataset are limited to specific pitched instruments, and there is a different amount and lenght of excerpts. Using this dataset When IRMAS is used for academic research, we would highly appreciate if scientific publications of works partly based on the IRMAS dataset quote the above publication. We are interested in knowing if you find our datasets useful! If you use our dataset please email us at [e-mail] and tell us about your research. https://www.upf.edu/web/mtg/irmas

本数据集包含带有主导乐器标注的音乐音频片段，曾用于下述论文的评估工作：Bosch, J. J.、Janer, J.、Fuhrmann, F. 与 Herrera, P. 发表于2012年国际音乐信息检索大会（Proc. ISMIR）的《音乐音频信号中主导乐器识别的声音分离技术比较》，原论文页码为559-564。
学术研究中请注明IRMAS数据集：IRMAS旨在用于音乐音频中主导乐器自动识别方法的训练与测试。
本次涵盖的乐器包括：大提琴（Cello）、单簧管（Clarinet）、长笛（Flute）、原声吉他（Acoustic Guitar）、电吉他（Electric Guitar）、管风琴（Organ）、钢琴（Piano）、萨克斯管（Saxophone）、小号（Trumpet）、小提琴（Violin）以及人声演唱（Human Singing Voice）。
本数据集源自Ferdinand Fuhrmann在其博士论文中整理的数据集，二者的区别在于：本次提供的音频数据为立体声格式，测试集的标注仅限定于特定有音高乐器，且片段的数量与长度均存在差异。
数据集使用须知：若您在学术研究中使用IRMAS数据集，我们恳请基于该数据集开展的研究成果在发表时引用上述论文。我们十分关注本数据集的应用价值，若您使用本数据集，请发送邮件至[e-mail]告知您的研究方向。更多信息可访问：https://www.upf.edu/web/mtg/irmas

搜集汇总

背景与挑战

背景概述

IRMAS数据集是一个专门用于音乐音频中主要乐器识别的数据集，包含11种乐器的标注音频片段，适用于训练和测试乐器识别算法。数据集来源于博士论文研究，提供了立体声音频和特定音高乐器的标注，总大小约11GB。