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The revolution in music distribution, storage, and consumption has fueled tremendous interest in developing techniques and tools for organizing, structuring, retrieving, navigating, and presenting music-related data. As a result, the academic field of music information retrieval (MIR) has matured over the last 20 years into an independent research area related to many different disciplines, including engineering, computer science, mathematics, and musicology. In this contribution, we introduce the Python package libfmp, which provides implementations of well-established model-based algorithms for various MIR tasks (with a focus on the audio domain), including beat tracking, onset detection, chord recognition, music synchronization, version identification, music segmentation, novelty detection, and audio decomposition. Such traditional approaches not only yield valuable baselines for modern data-driven strategies (e.g., using deep learning) but are also instructive from an educational viewpoint deepening the understanding of the MIR task and music data at hand. Our libfmp package is inspired and closely follows conventions as introduced by librosa, which is a widely used Python library containing standardized and flexible reference implementations of many common methods in audio and music processing While the two packages overlap concerning basic feature extraction and MIR algorithms, libfmp contains several reference implementations of advanced music processing pipelines not yet covered by librosa (or other open-source software). Whereas the librosa package is intended to facilitate the high-level composition of basic methods into complex pipelines, a major emphasis of libfmp is on the educational side, promoting the understanding of MIR concepts by closely following the textbook on Fundamentals of Music Processing (FMP) In this way, we hope that libfmp constitutes a valuable complement to existing open-source toolboxes such as librosa while fostering education and research in MIR.
Müller et al. (Tue,) studied this question.