musdb18曲目数据集

The sigsep musdb18 data set consists of a total of 150 full-track songs of different styles and includes both the stereo mixtures and the original sources, divided between a training subset and a test subset. Its purpose is to serve as a reference database for the design and the evaluation of source separation algorithms. The objective of such signal processing methods is to estimate one or more sources from a set of mixtures, e.g. for karaoke applications. It has been used as the official dataset in the professionally-produced music recordings task for SiSEC 2018, which is the international campaign for the evaluation of source separation algorithms. musdb18 contains two folders, a folder with a training set: “train”, composed of 100 songs, and a folder with a test set: “test”, composed of 50 songs. Supervised approaches should be trained on the training set and tested on both sets. All files from the musdb18 dataset are encoded in the Native Instruments stems format (.mp4). It is a multitrack format composed of 5 stereo streams, each one encoded in AAC @256kbps. These signals correspond to: For each file, the mixture correspond to the sum of all the signals. All signals are stereophonic and encoded at 44.1kHz. As the MUSDB18 is encoded as STEMS, it relies on ffmpeg to read the multi-stream files. We provide a python wrapper called stempeg that allows to easily parse the dataset and decode the stem tracks on-the-fly. If you use the MUSDB dataset for your research - Cite the MUSDB18 Dataset If compare your results with SiSEC 2018 Participants - Cite the SiSEC 2018 LVA/ICA Paper

sigsep musdb18数据集（sigsep musdb18 Dataset）总计包含150首不同风格的完整音乐曲目，同时提供立体声混合音频与原始分离声源，划分为训练子集与测试子集。其核心用途是作为声源分离算法设计与评估的参考数据库。此类信号处理方法的目标是从一组混合音频中估计出一个或多个声源，例如应用于卡拉OK场景。该数据集曾作为SiSEC 2018（国际声源分离算法评估赛事）官方指定的专业音乐录制任务数据集。

musdb18包含两个文件夹：名为"train"的训练集文件夹（收录100首曲目），以及名为"test"的测试集文件夹（收录50首曲目）。有监督学习方法应在训练集上完成模型训练，并在两个子集上开展测试。

musdb18数据集的所有文件均采用Native Instruments stems格式（.mp4）编码。该格式为多轨音频格式，包含5条立体声音频流，每条均采用AAC @256kbps编码。对于每个文件而言，混合音频为所有声源信号的总和。所有音频均为立体声格式，采样率为44.1kHz。

由于MUSDB18采用STEMS格式编码，因此需要借助ffmpeg工具读取多流文件。我们提供了名为stempeg的Python封装库，可便捷地解析该数据集并实时解码分轨曲目。

若您在研究工作中使用MUSDB数据集，请引用《MUSDB18 Dataset》；若您将研究结果与SiSEC 2018参赛作品进行对比，请引用《SiSEC 2018 LVA/ICA Paper》。

搜集汇总

背景与挑战

背景概述

musdb18曲目数据集是一个用于音乐分离算法评估的参考数据库，包含150首不同风格的全曲目，分为训练集和测试集。数据集以特定格式编码，包含混合音及四个分离的音轨（鼓声、贝斯声、其他伴奏声和人声），适用于信号处理研究和应用开发。