A cross-version approach for stabilizing tempo-based novelty detection - Müller, Meinard; Prätzlich, Thomas; Driedger, Jonathan (Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2012)

A Multi-Version Approach for Transferring Measure Annotations Between Music Recordings - Zalkow, Frank; Weiß, Christof; Prätzlich, Thomas; Arifi-Müller, Vlora; Müller, Meinard (Proceedings of the AES Conference on Semantic Audio, 2017)

Analyzing Measure Annotations for Western Classical Music Recordings - Weiß, Christof; Arifi-Müller, Vlora; Prätzlich, Thomas; Kleinertz, Rainer; Müller, Meinard (Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2016)

Automatisierte Identifikation von Audioaufnahmen anhand symbolisch codierter musikalischer Themen - Balke, Stefan; Lamprecht, Lukas; Arifi-Müller, Vlora; Prätzlich, Thomas; Müller, Meinard (Proceedings of the Deutsche Jahrestagung für Akustik (DAGA), 2015)

Brain Beats: Brain Beats: Tempo Extraction from EEG Data - Stober, Sebastian; Prätzlich, Thomas; Müller, Meinard (Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2016)

Cross-Version Singing Voice Detection in Classical Opera Recordings - Dittmar, Christian; Lehner, Bernhard; Prätzlich, Thomas; Müller, Meinard; Widmer, Gerhard (Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2015)

Das Gesamtkunstwerk Oper aus Datensicht - Aspekte des Umgangs mit einer heterogenen Datenlage im BMBF-Projekt ''Freischütz Digital'' - Röwenstrunk, Daniel; Prätzlich, Thomas; Betzwieser, Thomas; Müller, Meinard; Szwillus, Gerd; Veit, Joachim (Datenbank-Spektrum, 2015)

Frame-Level Audio Segmentation for Abridged Musical Works - Prätzlich, Thomas; Müller, Meinard (Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2014)

Freischütz Digital: a case study for reference-based audio segmentation of operas - Prätzlich, Thomas; Müller, Meinard (Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2013)

Freischütz Digital: a multimodal scenario for informed music processing - Müller, Meinard; Prätzlich, Thomas; Bohl, Benjamin W.; Veit, Joachim (Proceedings of the International Workshop on Image and Audio Analysis for Multimedia Interactive Services (WIAMIS), 2013)

Freischütz Digital: Demos of audio-related contributions - Prätzlich, Thomas; Müller, Meinard; Bohl, Benjamin W.; Veit, Joachim (Demos and Late Breaking News of the International Society for Music Information Retrieval Conference (ISMIR), 2015)

Freischütz Digital - When Computer Science Meets Musicology - Müller, Meinard; Prätzlich, Thomas; Dittmar, Christian (Festschrift für Joachim Veit zum 60. Geburtstag, 2016)

Kernel Additive Modeling for Interference Reduction in Multi-channel Music Recordings - Prätzlich, Thomas; Bittner, Rachel; Liutkus, Antoine; Müller, Meinard (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2015)

Known-Artist Live Song ID: A Hashprint Approach - Tsai, Timothy; Prätzlich, Thomas; Müller, Meinard (Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2016)

Known-Artist Live Song Identification Using Audio Hashprints - Tsai, Timothy; Prätzlich, Thomas; Müller, Meinard (IEEE Transactions on Multimedia, 2017)

Let It Bee - Towards NMF-Inspired Audio Mosaicing - Driedger, Jonathan; Prätzlich, Thomas; Müller, Meinard (Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2015)

Memory-Restricted Multiscale Dynamic Time Warping - Prätzlich, Thomas; Driedger, Jonathan; Müller, Meinard (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2016)

Score-Informed Audio Decomposition and Applications - Driedger, Jonathan; Grohganz, Harald; Prätzlich, Thomas; Ewert, Sebastian; Müller, Meinard (Proceedings of the ACM International Conference on Multimedia (ACM-MM), 2013)

Sync Toolbox: A Python Package for Efficient, Robust, and Accurate Music Synchronization - Müller, Meinard; Özer, Yigitcan; Krause, Michael; Prätzlich, Thomas; Driedger, Jonathan (Journal of Open Source Software, 2021)
Music can be described and represented in many different ways, including as sheet music, symbolic representations, and audio recordings (Müller, 2015). For each of these representations, different versions (e.g., recordings performed by different orchestras and conductors) that correspond to the same musical work may exist. Music information retrieval (MIR) aims at developing techniques and tools for organizing, understanding, and searching this information in a robust, efficient, and intelligent manner. In this context, various alignment and synchronization procedures have been developed with the common goal of automatically linking several types of music representations, thus coordinating the multiple information sources related to a given musical work. In the design and implementation of synchronization algorithms, one has to deal with a delicate tradeoff between efficiency, robustness, and accuracy—requirements leading to various approaches with many design choices. In this contribution, we introduce a Python package called Sync Toolbox that provides open-source reference implementations for full-fledged music synchronization pipelines and yields state-of-the-art alignment results for a wide range of Western music. Using suitable feature representations and cost measures, the toolbox’s core technology is based on dynamic time warping (DTW), which brings the feature sequences into temporal correspondence. To account for efficiency, robustness and, accuracy, our toolbox integrates and combines techniques such as multiscale DTW (MsDTW) (Müller et al., 2006; Salvador & Chan, 2004), memory-restricted MsDTW (MrMsDTW) (Prätzlich et al., 2016), and high-resolution music synchronization (Ewert et al., 2009). While realizing a complete system with presets that allow users to reproduce research results from the literature, our toolbox also provides well-documented functions for all basic building blocks required for feature extraction and alignment. Furthermore, the toolbox contains example code for visualizing, sonifying, and evaluating synchronization results, thus deepening the understanding of the techniques and dat

Towards Cross-Version Singing Voice Detection - Dittmar, Christian; Prätzlich, Thomas; Müller, Meinard (Proceedings of the Deutsche Jahrestagung für Akustik (DAGA), 2015)

Triple-Based Analysis of Music Alignments Without the Need of Ground-Truth Annotations - Prätzlich, Thomas; Müller, Meinard (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2016)