International Audio Laboratories Erlangen

Publications

  1. Christof Weiß, Hendrik Schreiber, and Meinard Müller
    Local Key Estimation in Music Recordings: A Case Study Across Songs, Versions, and Annotators
    IEEE/ACM Transactions on Audio, Speech & Language Processing, 28: 2919–2932, 2020. PDF Details DOI 
    @article{WeissSM20_LocalKey_TASLP,
author  = {Christof Wei{\ss} and Hendrik Schreiber and Meinard M{\"u}ller},
title   = {Local Key Estimation in Music Recordings: A Case Study Across Songs, Versions, and Annotators},
journal = {{IEEE/ACM} Transactions on Audio, Speech {\&} Language Processing},
volume  = {28},
number  = {},
pages   = {2919--2932},
year    = {2020},
doi     = {10.1109/TASLP.2020.3030485},
url-pdf = {https://ieeexplore.ieee.org/document/9222034},
url-details = {https://www.audiolabs-erlangen.de/resources/MIR/schubert-localkey}
}
  2. Hendrik Schreiber, Frank Zalkow, and Meinard Müller
    Modeling and Estimating Local Tempo: A Case Study on Chopin's Mazurkas
    In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR): 773–779, 2020. PDF 
    @inproceedings{SchreiberZM20_LocalTempoChopin_ISMIR,
author    = {Hendrik Schreiber and Frank Zalkow and Meinard M{\"u}ller},
title     = {Modeling and Estimating Local Tempo: {A} Case Study on {C}hopin's Mazurkas},
booktitle = {Proceedings of the International Society for Music Information Retrieval Conference ({ISMIR})},
address   = {Montr{\'{e}}al, Canada},
pages     = {773--779},
year      = {2020},
url-pdf   = {https://program.ismir2020.net/static/final_papers/14.pdf}
}
  3. Hendrik Schreiber, Julián Urbano, and Meinard Müller
    Music Tempo Estimation: Are We Done Yet?
    Transactions of the International Society for Music Information Retrieval (TISMIR), 3(1): 111–125, 2020. DOI 
    @article{SchreiberUM20_TempoEvaluation_TISMIR,
Author    = {Hendrik Schreiber and Juli{\'a}n Urbano and Meinard M{\"u}ller},
Doi       = {10.5334/tismir.43},
Journal   = {Transactions of the International Society for Music Information Retrieval  ({TISMIR})},
Number    = {1},
Pages     = {111--125},
Publisher = {Ubiquity Press},
Title     = {Music Tempo Estimation: Are We Done Yet?},
Volume    = {3},
Year      = {2020}}
  4. Hendrik Schreiber
    Data-Driven Approaches for Tempo and Key Estimation of Music Recordings
    PhD Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2020. Details 
    @phdthesis{Schreiber20_Thesis_PhD,
author      = {Hendrik Schreiber},
title       = {Data-Driven Approaches for Tempo and Key Estimation of Music Recordings},
type        = {doctoralthesis},
pages       = {188},
school      = {Friedrich-Alexander-Universit{\"a}t Erlangen-N{\"u}rnberg (FAU)},
year        = {2020},
url-details = {https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-141762},
}
  5. Hendrik Schreiber, Christof Weiß, and Meinard Müller
    Local Key Estimation in Classical Music Recordings: A Cross-Version Study on Schubert's Winterreise
    In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP): 501–505, 2020. PDF DOI 
    @inproceedings{SchreiberWM20_LocalKey_ICASSP,
author = {Hendrik Schreiber and Christof Wei{\ss} and Meinard M{\"u}ller},
title = {Local Key Estimation in Classical Music Recordings: A Cross-Version Study on {S}chubert's {W}interreise},
booktitle = {Proceedings of the {IEEE} International Conference on Acoustics, Speech, and Signal Processing ({ICASSP})},
address = {Barcelona, Spain},
pages = {501--505},
month = {May},
year = {2020},
url-pdf = {https://ieeexplore.ieee.org/document/9054642},
doi = {10.1109/ICASSP40776.2020.9054642}
}
  6. Dmitry Bogdanov, Alastair Porter, Hendrik Schreiber, Julián Urbano, Sergio Oramas
    The AcousticBrainz Genre Dataset: Multi-Source, Multi-Level, Multi-Label, and Large-Scale
    In Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2019. PDF 
    @inproceedings{BogdanovPSUO19_GenreAcousticBrainz_ISMIR,
title={The AcousticBrainz Genre Dataset: Multi-Source, Multi-Level, Multi-Label, and Large-Scale},
author={Dmitry Bogdanov, Alastair Porter, Hendrik Schreiber, Juli{\'a}n Urbano, Sergio Oramas},
address   = {Delft, The Netherlands},
booktitle = {Proceedings of the International Conference on Music Information Retrieval ({ISMIR})},
year={2019},
url-pdf = {http://archives.ismir.net/ismir2019/paper/000042.pdf}
}
  7. Jonathan Driedger, Hendrik Schreiber, Bas de Haas, Meinard Müller
    Towards Automatically Correcting Tapped Beat Annotations for Music Recordings
    In Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2019. PDF 
    @inproceedings{DriedgerSHM19_BeatTap_ISMIR,
title={Towards Automatically Correcting Tapped Beat Annotations for Music Recordings},
author={Jonathan Driedger, Hendrik Schreiber, Bas de Haas, Meinard M{\"u}ller},
address   = {Delft, The Netherlands},
booktitle = {Proceedings of the International Conference on Music Information Retrieval ({ISMIR})},
year={2019},
url-pdf = {http://archives.ismir.net/ismir2019/paper/000022.pdf}
}
  8. Hendrik Schreiber and Meinard Müller
    Musical Tempo and Key Estimation using Convolutional Neural Networks with Directional Filters
    In Proceedings of the 16th Sound and Music Computing Conference (SMC), 2019. PDF 
    @inproceedings{Schreiber2019directional,
title={Musical Tempo and Key Estimation using Convolutional Neural Networks with Directional Filters},
author={Hendrik Schreiber and Meinard M{\"u}ller},
address   = {Malaga, Spain},
booktitle = {Proceedings of the 16th Sound and Music Computing Conference ({SMC})},
year={2019},
url-pdf = {http://smc2019.uma.es/articles/P1/P1_07_SMC2019_paper.pdf}
}
  9. Hendrik Schreiber and Meinard Müller
    A Crowdsourced Experiment for Tempo Estimation of Electronic Dance Music
    In Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2018. PDF 
    @inproceedings{SchreiberM18a_Tempo_ISMIR,
author    = {Hendrik Schreiber and Meinard M{\"u}ller},
title     = {A Crowdsourced Experiment for Tempo Estimation of Electronic Dance Music},
booktitle = {Proceedings of the International Conference on Music Information Retrieval ({ISMIR})},
address   = {Paris, France},
year      = {2018},
url-pdf   = {http://www.tagtraum.com/download/2018_schreiber_tempo_giantsteps.pdf}
}
  10. Hendrik Schreiber and Meinard Müller
    A Single-Step Approach to Musical Tempo Estimation Using a Convolutional Neural Network
    In Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2018. PDF 
    @inproceedings{SchreiberM18b_Tempo_ISMIR,
author    = {Hendrik Schreiber and Meinard M{\"u}ller},
title     = {A Single-Step Approach to Musical Tempo Estimation Using a Convolutional Neural Network},
booktitle = {Proceedings of the International Conference on Music Information Retrieval ({ISMIR})},
address   = {Paris, France},
year      = {2018},
url-pdf   = {http://www.tagtraum.com/download/2018_schreiber_tempo_cnn.pdf}
}
  11. Dmitry Bogdanov, Alastair Porter, Julián Urbano, and Hendrik Schreiber
    The MediaEval 2018 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources
    In Proceedings of the MediaEval 2018 Multimedia Benchmark Workshop, 2018. PDF 
    @inproceedings{BogdanovPUS18_MediaEvalGenreTask,
author    = {Dmitry Bogdanov and Alastair Porter and Juli{\'a}n Urbano and Hendrik Schreiber},
title     = {The MediaEval 2018 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources},
booktitle = {Proceedings of the MediaEval 2018 Multimedia Benchmark Workshop},
address   = {Sophia Antipolis, France},
year      = {2018},
url-pdf   = {https://repositori.upf.edu/bitstream/handle/10230/35744/bogdanov_mediaeval_genre.pdf}
}
  12. Hendrik Schreiber
    A CNN baseline relying on Mel-Features
    In Proceedings of the MediaEval 2018 Multimedia Benchmark Workshop, 2018. PDF 
    @inproceedings{Schreiber18_GenreTaskBaseline_MediaEval,
author    = {Hendrik Schreiber},
title     = {A {CNN} baseline relying on Mel-Features},
booktitle = {Proceedings of the MediaEval 2018 Multimedia Benchmark Workshop},
address   = {Sophia Antipolis, France},
year      = {2018},
url-pdf   = {http://ceur-ws.org/Vol-2283/MediaEval_18_paper_30.pdf}
}
  13. Hendrik Schreiber
    Tempo and Meter Estimation for Greek Folk Music Using Convolutional Neural Networks and Transfer Learning
    In Technical Report for the 8th International Workshop on Folk Music Analysis (FMA), 2018. PDF 
    @inproceedings{Schreiber18_TempoMeter_FMA,
author    = {Hendrik Schreiber},
title     = {Tempo and Meter Estimation for Greek Folk Music Using Convolutional Neural Networks and Transfer Learning},
booktitle = {Technical Report for the 8th International Workshop on Folk Music Analysis ({FMA})},
address   = {Thessaloniki, Greece},
year      = {2018},
url-pdf   = {http://fma2018.mus.auth.gr/files/2018_SchreiberGreekFolkTempoMeter.pdf}
}
  14. Hendrik Schreiber
    CNN-based automatic musical key detection
    In Music Information Retrieval Evaluation eXchange (MIREX), 2017. PDF 
    @inproceedings{Schreiber17_KeyCNN_MIREX,
Address = {Suzhou, China},
Author = {Hendrik Schreiber},
Booktitle = {{M}usic {I}nformation {R}etrieval {E}valuation e{X}change {(MIREX)}},
Title = {{CNN}-based automatic musical key detection},
Year = {2017},
url-pdf = {https://www.music-ir.org/mirex/abstracts/2017/HS1.pdf}
}
  15. Hendrik Schreiber and Meinard Müller
    A Post-Processing Procedure for Improving Music Tempo Estimates Using Supervised Learning
    In Proceedings of the International Conference on Music Information Retrieval (ISMIR): 235–242, 2017. PDF 
    @inproceedings{SchreiberM17_Tempo_ISMIR,
author    = {Hendrik Schreiber and Meinard M{\"u}ller},
title     = {A Post-Processing Procedure for Improving Music Tempo Estimates Using Supervised Learning},
booktitle = {Proceedings of the International Conference on Music Information Retrieval ({ISMIR})},
address   = {Suzhou, China},
year      = {2017},
pages     = {235--242},
url-pdf   = {https://ismir2017.smcnus.org/wp-content/uploads/2017/10/137_Paper.pdf}
}
  16. Dmitry Bogdanov, Alastair Porter, Julián Urbano, and Hendrik Schreiber
    The MediaEval 2017 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources
    In Working Notes Proceedings of the MediaEval 2017 Workshop co-located with the Conference and Labs of the Evaluation Forum (CLEF 2017), 2017. PDF 
    @inproceedings{BogdanovPUS17_MediaEvalGenreTask_CLEF,
author    = {Dmitry Bogdanov and Alastair Porter and Juli{\'a}n Urbano and Hendrik Schreiber},
title     = {The MediaEval 2017 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources},
booktitle = {Working Notes Proceedings of the MediaEval 2017 Workshop co-located
with the Conference and Labs of the Evaluation Forum {(CLEF} 2017)},
address   = {Dublin, Ireland},
year      = {2017},
url-pdf   = {http://slim-sig.irisa.fr/me17/Mediaeval_2017_paper_6.pdf}
}
  17. Hendrik Schreiber
    Genre Ontology Learning: Comparing Curated with Crowd-Sourced Ontologies
    In Proceedings of the International Conference on Music Information Retrieval (ISMIR): 400–406, 2016. PDF 
    @inproceedings{Schreiber16_GenreOntologyLearning_ISMIR,
author    = {Hendrik Schreiber},
title     = {Genre Ontology Learning: Comparing Curated with Crowd-Sourced Ontologies},
pages     = {400--406},
booktitle = {Proceedings of the International Conference on Music Information Retrieval ({ISMIR})},
address   = {New York, USA},
year      = {2016},
url-pdf   = {https://pdfs.semanticscholar.org/4540/ba0e1b4c4f404f2bcdd9bc91cbd46d02b856.pdf}
}
  18. Hendrik Schreiber
    Improving Genre Annotations for the Million Song Dataset
    In Proceedings of the International Conference on Music Information Retrieval (ISMIR): 241–247, 2015. PDF 
    @inproceedings{Schreiber15_GenreAnnotationsMSD_ISMIR,
author    = {Hendrik Schreiber},
title     = {Improving Genre Annotations for the Million Song Dataset},
pages     = {241--247},
booktitle = {Proceedings of the International Conference on Music Information Retrieval ({ISMIR})},
address   = {M{\'a}laga, Spain},
year      = {2015},
url-pdf   = {http://ismir2015.uma.es/articles/102_Paper.pdf}
}
  19. Hendrik Schreiber and Meinard Müller
    Accelerating Index-Based Audio Identification
    IEEE Transactions on Multimedia, 16(6): 1654–1664, 2014. DOI 
    @article{SchreiberMueller14_AudioID_IEEE-TMM,
author    = {Hendrik Schreiber and Meinard M{\"u}ller},
title     = {Accelerating Index-Based Audio Identification},
journal   = {{IEEE} Transactions on Multimedia},
volume    = {16},
number    = {6},
pages     = {1654--1664},
year      = {2014},
doi       = {10.1109/TMM.2014.2318517}
}
  20. Hendrik Schreiber and Meinard Müller
    Exploiting Global Features for Tempo Octave Correction
    In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP): 639–643, 2014. PDF 
    @inproceedings{SchreiberM14_TempoCorrecetion_ICASSP,
author     = {Hendrik Schreiber and Meinard M{\"u}ller},
title      = {Exploiting Global Features for Tempo Octave Correction},
booktitle  = {Proceedings of the {IEEE} International Conference on Acoustics, Speech, and Signal Processing ({ICASSP})},
address    = {Florence, Italy},
pages      = {639--643},
year       = {2014},
url-pdf    = {https://www.audiolabs-erlangen.de/fau/professor/mueller/publications/2014_SchreiberMueller_TempoEstimation_ICASSP.pdf}
}
  21. Hendrik Schreiber, Peter Grosche, and Meinard Müller
    A Re-ordering Strategy for Accelerating Index-based Audio Fingerprinting
    In Proceedings of the International Conference on Music Information Retrieval (ISMIR): 127–132, 2011. PDF 
    @inproceedings{SchreiberGM11_FingerPrint_ISMIR,
author    = {Hendrik Schreiber and Peter Grosche and Meinard M{\"u}ller},
title     = {A Re-ordering Strategy for Accelerating Index-based Audio Fingerprinting},
booktitle = {Proceedings of the International Conference on Music Information Retrieval ({ISMIR})},
address   = {Miami, Florida, USA},
year      = {2011},
pages     = {127--132},
url-pdf   = {http://www.ismir2011.ismir.net/papers/PS1-15.pdf}
}
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