Profile

W. Bas de Haas finished his PhD thesis at Utrecht University in 2011. He works on Music Information Retrieval and specifically focuses on developing methods that are founded in music cognition and perception. Most of his contributions are concerned with the analysis and similarity of tonal harmony. Currently, Bas is involved in the MUSIVA project which investigates music similarity grounded in variation.

Gegenereerd op 2017-09-26 12:48:17

Thesis
De Haas, W.B. (2012), Music information retrieval based on tonal harmony. PhD thesis. Utrecht University.

Abstract
With the emergence of large scale digitalisation of music, content-based methods to maintain, structure, and provide access to digital music repositories have become increasingly important. This doctoral dissertation covers a wide range of methods that aim to aid in the organisation of music information. From both a practical as well as cognitive point of view, it is logical to structure musical content by defining similarity relations between documents. Consequently, the notion of music similarity has become a fundamental concept within the area music information retrieval (MIR) research. In this dissertation we study a particular type of music similarity: the similarity of musical harmony.

Because both musically trained and untrained listeners have extensive knowledge about music, it is rather unlikely that all information needed for sound similarity judgement can be found in the musical information source alone. Therefore, to be able to place chord sequences in the context of Western tonal harmony, we investigate two approaches towards automatic harmony analysis. Although the first generative grammar-based solution yields good results on a small dataset, it exposed some practical challenges that prevented it to be extended to process larger datasets. Hence, the second harmonic analysis solution exploits state-of-the-art functional programming techniques, like type-level computation and error-correcting parsers, to meet these challenges. This model, named HarmTrace, is fast, flexible, and returns analyses that are in accordance with harmony theory. We evaluate these harmonic annotations, which explain the role of a chord in its tonal context, both qualitatively as well as quantitatively, and show how they can aid in harmonic similarity estimation and automatic chord transcription.

We investigate three novel approaches to harmonic similarity: a geometric, a local alignment, and a common embeddable subtree based approach. The geometric approach, named TPSD, uses a music theoretically motivated step functions to assess the similarity of two chord sequences; the common embeddable subtree approach estimates harmonic similarity by matching hierarchical harmonic analysis annotations; and the local alignment solution uses context-aware substitution functions to align sequences of chords. For each of these harmonic similarity solutions, the adjustable parameters are discussed and evaluated. For the evaluation a large new chord sequence corpus is assembled consisting of 5028 different chord sequences, some of which describe the same song. The results show that an alignment approach that uses the HarmTrace harmony model performs best in retrieving these similar chord sequences. All proposed similarity measures rely on the availability of sequences of symbolic chord labels. To extend the application domain, we demonstrate how automatic chord transcription from musical audio can be improved by exploiting our model of tonal harmony

All publications
  2017 - Scholarly publications
Koops, Hendrik Vincent, de Haas, W.B., Bransen, J. & Volk, A. (18.05.2017). Chord Label Personalization through Deep Learning of Integrated Harmonic Interval-based Representations. In Dorien Herremans & Ching-Hua Chuan (Eds.), Proceedings of the first International Workshop on Deep Learning and Music (pp. 19-25) (7 p.). Anchorage, Alaska, USA.
  2016 - Scholarly publications
Boot, Peter, Volk, A. & de Haas, W.B. (2016). Evaluating the Role of Repeated Patterns in Folk Song Classification and Compression. Journal of New Music Research, 45 (3), (pp. 223-238) (16 p.).
Koops, Hendrik Vincent, de Haas, W.B., Bountouridis, D. & Volk, A. (2016). Integration And Quality Assessment Of Heterogeneous Chord Sequences Using Data Fusion. International Society for Music Information Retrieval Conference (pp. 178-184) (7 p.).
de Haas, W.B. & Volk, A. (09.08.2016). Meter Detection in Symbolic Music Using Inner Metric Analysis. International Society for Music Information Retrieval Conference (pp. 441) (447 p.). New York.
  2015 - Scholarly publications
Koops, Hendrik Vincent, Volk, A. & de Haas, W.B. (26.10.2015). Corpus-Based Rhythmic Pattern Analysis of Ragtime Syncopation. In Meinard Müller & Frans Wiering (Eds.), Proceedings of the 16th International Society for Music Information Retrieval Conference, ISMIR 2015 (pp. 483-489) (7 p.). Málaga, Spain: ISMIR press.
  2014 - Scholarly publications
Rodríguez López, M.E., de Haas, Bas & Volk, Anja (2014). Comparing repetition-based melody segmentation models. Proceedings of the 9th Conference on Interdisciplinary Musicology (CIM14) (pp. 143-148) (6 p.). Berlin: SIMPK and ICCMR.
Burgoyne, J. Ashley, de Haas, W. Bas & Pauwels, Johan (2014). On Comparative Statistics for Labelling Tasks: What can We Learn from MIREX ACE 2013. In Hsin-Min Wang , Yi-Hsuan Yang & Jin Ha Lee (Eds.), Proceedings of the 15th Conference of the International Society for Music Information Retrieval (ISMIR 2014) - October 27 - 31, 2014 Taipei, Taiwan (pp. 525-530) (6 p.).
van Herwaarden, Sam, Grachten, Maarten & de Haas, W. Bas (2014). Predicting Expressive Dynamics in Piano Performances using Neural Networks. In Hsin-Min Wang , Yi-Hsuan Yang & Jin Ha Lee (Eds.), Proceedings of the 15th Conference of the International Society for Music Information Retrieval (ISMIR 2014) - October 27 - 31, 2014 Taipei, Taiwan (pp. 45-52) (6 p.). International Society for Music Information Retrieval.
  2013 - Scholarly publications
Volk, A. & de Haas, W.B. (2013). A corpus-based study on ragtime syncopation. Proceedings of the International Society for Music Information Retrieval Conference volk2013.
Koops, Hendrik Vincent, Rodrigues Magalhães, J.P. & de Haas, W.B. (2013). A Functional Approach to Automatic Melody Harmonisation. Proceedings of the first ACM SIGPLAN workshop on Functional art, music, modeling and design (pp. 47-58) (12 p.). New York, NY, USA: ACM, Koops2013.
de Haas, W.B., Wiering, F. & Veltkamp, R.C. (2013). A geometrical distance measure for determining the similarity of musical harmony. International Journal of Multimedia Information Retrieval, 2 (3), (pp. 189-202) (14 p.).
de Haas, W.B., Magalhães, J.P., Wiering, F. & Veltkamp, R.C. (2013). Automatic Functional Harmonic Analysis. Computer Music Journal, 37 (4), (pp. 37-53) (17 p.).
Jansen, B., de Haas, W.B., Volk, A. & van Kranenburg, P. (2013). Discovering repeated patterns in music: state of knowledge, challenges, perspectives. 10th International Symposium on Computer Music Multidisciplinary Research (CMMR) janssen2013.
de Haas, W.B., Volk, A. & Wiering, F. (2013). Structural segmentation of music based on repeated harmonies. Proceedings of the International Symposium on Multimedia (pp. 255-258) (4 p.). Anaheim: IEEE.
  2012 - Scholarly publications
de Haas, W.B., Rodrigues Magalhães, J.P. & Wiering, F. (2012). Improving audio chord transcription by exploiting harmonic and metric knowledge. 13th International Society for Music Information Retrieval Conference (ISMIR 2012) (pp. 295-300) (6 p.). Porto.
Volk, A., de Haas, W.B. & van Kranenburg, P. (2012). Towards Modelling Variation in Music as a Foundation for Similarity. Proceedings of the 12th International Conference on Music Perception and Cognition (pp. 1085-1094) (10 p.). Aristotle University of Thessaloniki, Volk12:ICMPC.
  2011 - Scholarly publications
Rodrigues Magalhães, J.P. & de Haas, W.B. (2011). Functional Modelling of Musical Harmony--An experience report. Proceedings of the 16th ACM SIGPLAN International Conference on Functional Programming Tokyo, Japan.
de Haas, W.B., Rodrigues Magalhães, J.P., Veltkamp, R.C. & Wiering, F. (2011). HarmTrace: Improving harmonic similarity estimation using functional harmony analysis. Proceedings of the 12th International Conference on Music Information Retrieval (ISMIR) Miami, U.S.A..
  2010 - Scholarly publications
de Haas, W.B., Robine, M., Hanna, P., Veltkamp, R.C. & Wiering, F. (2010). Comparing Harmonic Similarity Measures. 7th International Symposium on Computer Music Modeling and Retrieval (pp. 299-315) (17 p.). Malaga.
de Haas, W.B. & Wiering, F. (2010). Hooked on music information retrieval. Empirical Musicology Review, 5 (4), (pp. 176-185) (10 p.). haas2010mir.
  2009 - Scholarly publications
de Haas, W.B., Rohrmeier, M., Veltkamp, R.C. & Wiering, F. (2009). Modeling Harmonic Similarity Using a Generative Grammar of Tonal Harmony. Proceedings of the Tenth International Conference on Music Information Retrieval (ISMIR) International Conference on Music Information Retrieval (ISMIR).
  2008 - Scholarly publications
Honing, H. & de Haas, W.B. (2008). Swing Once More: Relating Timing and Tempo in Expert Jazz Drumming. Music Perception, 25 (5), (pp. 471-476) (6 p.).
de Haas, W.B., Veltkamp, R.C. & Wiering, F. (2008). Tonal Pitch Step Distance: a Similarity Measure for Chord Progressions. Proceedings of the Eighth International Conference on Music Information Retrieval (ISMIR) haas08:tpsd.
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Gegenereerd op 2017-09-26 12:48:17

W. Bas de Haas is interested in the development and application of music technology. Can we create search engines that help us organise the immense amount of musical information on the Internet? Can we design a computer program that automatically transforms a piece of music into a score? These are typical questions in which Bas is interested.

Gegenereerd op 2017-09-26 12:48:17
Additional functions and activities

Besides his postdoc job at Utrecht University, W. Bas de Haas has started the music technology start-up Chordify together with Tijmen Ruizendaal, Gijs Bekenkamp, Dion ten Heggeler, and José Pedro Magalhães

Chordify is a free on-line music player that quickly converts SoundCloud, YouTube or your own music files into chords. The integrated music player follows the chords at every beat and makes it easy to play along. Chordify is an innovative tool that novice and experienced musicians can use to practise and play their favourite music. The tool is intuitive, simple to use, and also looks pretty.

For more information please see: chordify.net

Gegenereerd op 2017-09-26 12:48:17
Full name
dr. W.B. de Haas Contact details
Buys Ballotgebouw

Princetonplein 5
Room BBL-486
3584 CC  UTRECHT
The Netherlands


Phone number (direct) +31 30 253 5965
Phone number (department) +31 30 253 4109
Buys Ballotgebouw

Princetonplein 5
Room BBL 486
3584 CC  UTRECHT
The Netherlands


Phone number (direct) +31 30 253 2952
Phone number (department) +31 30 253 4109
Postal address
Postbus 80.089
3508 TB    UTRECHT
The Netherlands
Gegenereerd op 2017-09-26 12:48:17
Last updated 25.08.2017