| librosa/librosa: 0.8. 0 B McFee, V Lostanlen, A Metsai, M McVicar, S Balke, C Thomé, C Raffel, ... Version 0.8. 0, Zenodo, doi 10, 2020 | 104 | 2020 |
| Theme transformer: Symbolic music generation with theme-conditioned transformer YJ Shih, SL Wu, F Zalkow, M Müller, YH Yang IEEE Transactions on Multimedia 25, 3495-3508, 2022 | 75 | 2022 |
| viktorandreevichmorozov, K B McFee, A Metsai, M McVicar, S Balke, C Thomé, C Raffel, F Zalkow, ... Moore, R. Bittner, S. Hidaka, Z. Wei, nullmightybofo, D. Herenú, F.-R …, 2020 | 58 | 2020 |
| FMP Notebooks: Educational Material for Teaching and Learning Fundamentals of Music Processing. M Müller, F Zalkow ISMIR, 573-580, 2019 | 48 | 2019 |
| A comparison of recent neural vocoders for speech signal reconstruction P Govalkar, J Fischer, F Zalkow, C Dittmar Proc. 10th ISCA speech synthesis workshop, 7-12, 2019 | 48 | 2019 |
| Schubert Winterreise dataset: A multimodal scenario for music analysis C Weiß, F Zalkow, V Arifi-Müller, M Müller, HV Koops, A Volk, ... Journal on Computing and Cultural Heritage (JOCCH) 14 (2), 1-18, 2021 | 46 | 2021 |
| librosa/librosa: 0.7. 2 B McFee, V Lostanlen, M McVicar, A Metsai, S Balke, C Thomé, C Raffel, ... Zenodo, Jan 13, 2020 | 44 | 2020 |
| librosa/librosa: 0.9. 1 B McFee, A Metsai, M McVicar, S Balke, C Thomé, C Raffel, F Zalkow, ... Zenodo, 2022 | 32 | 2022 |
| librosa/librosa: 0.6. 3 B McFee, M McVicar, S Balke, V Lostanlen, C Thom, C Raffel, D Lee, ... URL: https://doi. org/10.5281/zenodo 2564164, 2019 | 24 | 2019 |
| nullmightybofo, P. Friesch, F B McFee, M McVicar, S Balke, V Lostanlen, C Thom, C Raffel, D Lee, ... R. Stter, Thassilo, M. Vollrath, SK Golu, nehz, S. Waloschek, Seth, R …, 2019 | 22 | 2019 |
| libfmp: A Python package for fundamentals of music processing M Müller, F Zalkow Journal of Open Source Software 6 (63), 3326, 2021 | 21 | 2021 |
| Learning low-dimensional embeddings of audio shingles for cross-version retrieval of classical music F Zalkow, M Müller Applied Sciences 10 (1), 19, 2019 | 21 | 2019 |
| A multi-version approach for transferring measure annotations between music recordings F Zalkow, C Weiß, T Prätzlich, V Arifi-Müller, M Müller Audio Engineering Society Conference: 2017 AES International Conference on …, 2017 | 19 | 2017 |
| Modeling and Estimating Local Tempo: A Case Study on Chopin's Mazurkas. H Schreiber, F Zalkow, M Müller ISMIR, 773-779, 2020 | 18 | 2020 |
| Exploring Tonal-Dramatic Relationships in Richard Wagner's Ring Cycle. F Zalkow, C Weiß, M Müller ISMIR, 642-648, 2017 | 16 | 2017 |
| Using Weakly Aligned Score-Audio Pairs to Train Deep Chroma Models for Cross-Modal Music Retrieval. F Zalkow, M Müller ISMIR, 184-191, 2020 | 15 | 2020 |
| Classifying Leitmotifs in Recordings of Operas by Richard Wagner. M Krause, F Zalkow, J Zalkow, C Weiß, M Müller ISMIR, 473-480, 2020 | 14 | 2020 |
| CTC-based learning of chroma features for score–audio music retrieval F Zalkow, M Müller IEEE/ACM Transactions on Audio, Speech, and Language Processing 29, 2957-2971, 2021 | 13 | 2021 |
| Versionsübergreifende Visualisierung harmonischer Verläufe C Weiß, F Zalkow, M Müller, S Klauk, R Kleinertz Gesellschaft für Informatik, Bonn, 2017 | 13 | 2017 |
| Musical style modification as an optimization problem SAP SE Proceedings of the International Computer Music Conference, 206, 2016 | 13 | 2016 |
Meinard MüllerInternational Audio Laboratories Erlangen, Friedrich-Alexander-Universität Erlangen-NürnbergVerified email at audiolabs-erlangen.de