This paper introduces an extendable modular system that compiles a range of music feature extraction models to aid music information retrieval research. The features include musical elements like key, downbeats, and genre, as well as audio characteristics like instrument recognition, vocals/instrumental classification, and vocals gender detection. The integrated models are state-of-the-art or latest open-source. The features can be extracted as latent or post-processed labels, enabling integration into music applications such as generative music, recommendation, and playlist generation. The modular design allows easy integration of newly developed systems, making it a good benchmarking and comparison tool. This versatile toolkit supports the research community in developing innovative solutions by providing concrete musical features.

翻译：本文介绍了一个可扩展的模块化系统，该系统整合了一系列音乐特征提取模型，以支持音乐信息检索研究。所提取的特征既包括调性、强拍、流派等音乐元素，也涵盖乐器识别、人声/器乐分类以及人声性别检测等音频特性。系统集成的模型均为当前最先进或最新的开源模型。这些特征可以潜在特征或后处理标签的形式提取，便于集成到生成音乐、推荐系统及播放列表生成等音乐应用中。其模块化设计便于新开发系统的轻松集成，使其成为良好的基准测试与比较工具。该多功能工具包通过提供具体的音乐特征，支持研究社区开发创新解决方案。