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  • 1. Agres, K. R.
    et al.
    Schaefer, R. S.
    Volk, A.
    van Hooren, S.
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Dalla Bella, S.
    Müller, M.
    de Witte, M.
    Herremans, D.
    Ramirez Melendez, R.
    Neerincx, M.
    Ruiz, S.
    Meredith, D.
    Dimitriadis, T.
    Magee, W. L.
    Music, Computing, and Health: A Roadmap for the Current and Future Roles of Music Technology for Health Care and Well-Being2021In: Music & Science, E-ISSN 2059-2043, Vol. 4Article in journal (Refereed)
    Abstract [en]

    The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the involved disciplines, the workshop “Music, Computing, and Health” was held to discuss best practices and state-of-the-art at the intersection of these areas with researchers from music psychology and neuroscience, music therapy, music information retrieval, music technology, medical technology (medtech), and robotics. Following the discussions at the workshop, this article provides an overview of the different methods of the involved disciplines and their potential contributions to developing music technology for health and well-being. Furthermore, the article summarizes the state of the art in music technology that can be applied in various health scenarios and provides a perspective on challenges and opportunities for developing music technology that (1) supports person-centered care and evidence-based treatments, and (2) contributes to developing standardized, large-scale research on music-based interventions in an interdisciplinary manner. The article provides a resource for those seeking to engage in interdisciplinary research using music-based computational methods to develop technology for health care, and aims to inspire future research directions by evaluating the state of the art with respect to the challenges facing each field.

  • 2. Agres, Kat Rose
    et al.
    Schaefer, Rebecca
    Volk, Anja
    van Hooren, Susan
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Dalla Bella, Simone
    Mueller, Meinard
    de Witte, Martina
    Herremans, Dorien
    Ramirez Melendez, Rafael
    Neerincx, Mark A.
    Ruiz, Sebastian
    Meredith, David
    Dimitriadis, Theo
    Magee, Wendy L.
    Music, Computing, and Health: A roadmap for the current and future roles of music technology for health care and well-being2021Manuscript (preprint) (Other academic)
  • 3.
    Andersson López, Lisa
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Svenns, Thelma
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Sensitiv – Designing a Sonic Co-play Tool for Interactive Dance2021In: Proceedings International Conference on New Interfaces for Musical Expression  2021, PubPub , 2021Conference paper (Refereed)
    Abstract [en]

    In the present study a musician and a dancer explore the co-play between themthrough sensory technology. The main questions concern the placement andprocessing of motion sensors, and the choice of sound parameters that a dancer canmanipulate. Results indicate that sound parameters of delay and pitch altered dancers’experience most positively and that placement of sensors on each wrist and ankle witha diagonal mapping of the sound parameters was the most suitable.

  • 4. Benetos, Emmanouil
    et al.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Automatic Transcription of Turkish Makam Music2013In: Proceedings of ISMIR - International Conference on Music Information Retrieval, International Society for Music Information Retrieval, 2013, p. 355-360Conference paper (Refereed)
    Abstract [en]

    In this paper we propose an automatic system for transcribing makam music of Turkey. We document the specific traits of this music that deviate from properties that were targeted by transcription tools so far and we compile a dataset of makam recordings along with aligned microtonal ground-truth. An existing multi-pitch detection algorithm is adapted for transcribing music in 20 cent resolution, and the final transcription is centered around the tonic frequency of the recording. Evaluation metrics for transcribing microtonal music are utilized and results show that transcription of Turkish makam music in e.g. an interactive transcription software is feasible using the current state-of-the-art.

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  • 5. Benetos, Emmanouil
    et al.
    Holzapfel, André
    Department of Computer Engineering, Boğaziçi University, 34342 Bebek, Istanbul, Turkey.
    Automatic transcription of Turkish microtonal music2015In: Journal of the Acoustical Society of America, ISSN 0001-4966, Vol. 138, no 4, p. 2118-2130Article in journal (Refereed)
    Abstract [en]

    Automatic music transcription, a central topic in music signal analysis, is typically limited to equal-tempered music and evaluated on a quartertone tolerance level. A system is proposed to automatically transcribe microtonal and heterophonic music as applied to the makam music of Turkey. Specific traits of this music that deviate from properties targeted by current transcription tools are discussed, and a collection of instrumental and vocal recordings is compiled, along with aligned microtonal reference pitch annotations. An existing multi-pitch detection algorithm is adapted for transcribing music with 20 cent resolution, and a method for converting a multi-pitch heterophonic output into a single melodic line is proposed. Evaluation metrics for transcribing microtonal music are applied, which use various levels of tolerance for inaccuracies with respect to frequency and time. Results show that the system is able to transcribe microtonal instrumental music at 20 cent resolution with an F-measure of 56.7%, outperforming state-of-the-art methods for the same task. Case studies on transcribed recordings are provided, to demonstrate the shortcomings and the strengths of the proposed method.

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  • 6. Benetos, Emmanouil
    et al.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Incorporating pitch class profiles for improving automatic transcription of Turkish makam music2014In: Proceedings of the 4th Workshop on Folk Music Analysis, Computer Engineering Department, Bogaziçi University , 2014, p. 15-20Conference paper (Refereed)
    Abstract [en]

    In this paper we evaluate the impact of including knowledge about scale material into a system for the transcription of Turkish makam music. To this end, we extend our previously presented appoach by a refinement iteration that gives preference to note values present in the scale of the mode (i.e. makam). The information about the scalar material is provided in form of pitch class profiles, and they are imposed in form of a Dirichlet prior to our expanded probabilistic latent component analysis (PLCA) transcription system. While the inclusion of such a prior was supposed to focus the transcription system on musically meaningful areas, the obtained results are significantly improved only for recordings of certain instruments. In our discussion we demonstrate the quality of the obtained transcriptions, and discuss the difficulties caused for evaluation in the context of microtonal music.

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  • 7. Benetos, Emmanouil
    et al.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Stylianou, Yannis
    Pitched Instrument Onset Detection Based on Auditory Spectra2009In: Proceedings of ISMIR - International Conference on Music Information Retrieval, 2009, p. 105-110Conference paper (Refereed)
    Abstract [en]

    In this paper, a novel method for onset detection of music signals using auditory spectra is proposed. The auditory spectrogram provides a time-frequency representation that employs a sound processing model resembling the human auditory system. Recent work on onset detection employs DFT-based features, such as the spectral flux and group delay function. The spectral flux and group delay are introduced in the auditory framework and an onset detection algorithm is proposed. Experiments are conducted on a dataset covering 11pitched instrument types, consisting of 1829 onsets in total. Results indicate the superiority of the auditory representations over the DFT-based ones, with the auditory spectral flux exhibiting an onset detection improvement by 2% in terms of F-measure when compared to the DFT-based feature.

  • 8. Bozkurt, Baris
    et al.
    Ayangil, Ruhi
    Holzapfel, André
    Bahçeşehir University, Istanbul, Turkey.
    Computational analysis of makam music in Turkey: review of state-of-the-art and challenges2014In: Journal of New Music Research, ISSN 0929-8215, E-ISSN 1744-5027, Journal for New Music Research, Vol. 43, no 1, p. 3-23Article in journal (Refereed)
    Abstract [en]

    This text targets a review of the computational analysis literature for Turkish makam music, discussing in detail the challenges involved and presenting a perspective for further studies. For that purpose, the basic concepts of Turkish makam music and the description of melodic, rhythmic and timbral aspects are considered in detail. Studies on tuning analysis, automatic transcription, automatic melodic analysis, automatic makam and usul detection are reviewed. Technological and data resource needs for further advancement are discussed and available sources are presented.

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  • 9.
    Bresin, Roberto
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Falkenberg, Kjetil
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Pauletto, Sandra
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    KTH Royal Institute of Technology - Sound and Music Computing (SMC) Group2021In: Proceedings of the Sound and Music Computing Conferences 2021, Sound and Music Computing Network , 2021, p. xxv-xxviConference paper (Other academic)
  • 10.
    Clemente, Ana
    et al.
    Human Evolution and Cognition Research Group, University of the Balearic Islands, Spain;Department of Cognition, Development and Educational Psychology, Institute of Neurosciences, University of Barcelona, Spain.
    Friberg, Anders
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Relations between perceived affect and liking for melodies and visual designs.2023In: Emotion, ISSN 1528-3542, E-ISSN 1931-1516, Vol. 23, no 6, p. 1584-1605Article in journal (Refereed)
    Abstract [en]

    Sensory valuation is a fundamental aspect of cognition. It involves assigning hedonic value to a stimulus based on its sensory information considering personal and contextual factors. Hedonic values (e.g., liking) can be deemed affective states that motivate behavior, but the relations between hedonic and affective judgments have yet to be established. To fill this gap, we investigated the relations between stimulus features, perceived affect, and liking across domains and with potentially relevant individual traits. Fifty-eight participants untrained in music and visual art rated their liking and perceived valence and arousal for visual designs and short melodies varying in balance, contour, symmetry, or complexity and filled out several questionnaires. First, we examined group-level relations between perceived affect and liking across domains. Second, we inspected the relations between the individual use of musical and visual properties in judgments of liking and perceived affect-that is, between aesthetic and perceived-affect sensitivities. Third, we inquired into the influence of information-related (need for cognition, or NFC) and affect-related (need for emotion) traits on individual sensitivities. We found domain-specific effects of the stimulus features on liking, a linear association between valence and liking, the inverted-U model of arousal and liking, a binary profile of musical aesthetic sensitivities, and a modulatory effect of NFC on how people use stimulus properties in their hedonic and affective judgments. In summary, the results suggest that hedonic value is primarily computed from domain-specific sensory information partially moderated by NFC. 

  • 11. Cornelis, Olmo
    et al.
    Six, Joren
    Holzapfel, André
    Bahçeşehir University, Turkey.
    Leman, Marc
    Evaluation and Recommendation of Pulse and Tempo Annotation in Ethnic Music2013In: Journal for New Music Research, ISSN 0929-8215, Vol. 42, no 2, p. 131-149Article in journal (Refereed)
    Abstract [en]

    Large digital archives of ethnic music require automatic tools to provide musical content descriptions. While various automatic approaches are available, they are to a wide extent developed for Western popular music. This paper aims to analyse how automated tempo estimation approaches perform in the context of Central-African music. To this end we collect human beat annotations for a set of musical fragments, and compare them with automatic beat tracking sequences. We first analyse the tempo estimations derived from annotations and beat tracking results. Then we examine an approach, based on mutual agreement between automatic and human annotations, to automate such analysis, which can serve to detect musical fragments with high tempo ambiguity.

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  • 12. d’Alessandro, N.
    et al.
    Babacan, O.
    Bozkurt, B.
    Dubuisson, T.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Kessous, L.
    Moinet, A.
    Vlieghe, M.
    Dutoit, T.
    RAMCESS 2.x FRAMEWORK - EXPRESSIVE VOICE ANALYSIS FOR REALTIME AND ACCURATE SYNTHESIS OF SINGING2008In: Journal on Multimodal User Interfaces, ISSN 1783-7677, Vol. 2, p. 133-144Article in journal (Refereed)
    Abstract [en]

    In this paper we present the work that has been achieved in the context of the second version of the RAMCESS singing synthesis framework. The main improvement of this study is the integration of new algorithms for expressive voice analysis, especially the separation of the glottal source and the vocal tract. Realtime synthesis modules have also been refined. These elements have been integrated in an existing digital instrument: the HANDSKETCH 1.X, a bimanual controller. Moreover this digital instrument is compared to existing systems.

  • 13. de Valk, Reinier
    et al.
    Volk, Anja
    Utrecht University.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Pikrakis, Aggelos
    Kroher, Nadine
    Six, Joren
    MIRchiving: Challenges and opportunities of connecting MIR research and digital music archives2017In: DLfM '17 Proceedings of the 4th International Workshop on Digital Libraries for Musicology, ACM Digital Library, 2017Conference paper (Refereed)
    Abstract [en]

    This study is a call for action for the music information retrieval (MIR) community to pay more attention to collaboration with digital music archives. The study, which resulted from an interdisciplinary workshop and subsequent discussion, matches the demand for MIR technologies from various archives with what is already supplied by the MIR community. We conclude that the expressed demands can only be served sustainably through closer collaborations. Whereas MIR systems are described in scientific publications, usable implementations are often absent. If there is a runnable system, user documentation is often sparse---posing a huge hurdle for archivists to employ it. This study sheds light on the current limitations and opportunities of MIR research in the context of music archives by means of examples, and highlights available tools. As a basic guideline for collaboration, we propose to interpret MIR research as part of a value chain. We identify the following benefits of collaboration between MIR researchers and music archives: new perspectives for content access in archives, more diverse evaluation data and methods, and a more application-oriented MIR research workflow.

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  • 14.
    Dignum, Virginia
    et al.
    Umeå University - Department Of Computing Science.
    Casey, Donal
    Kent Law School, University of Kent.
    Dignum, Frank
    Umeå University - Department Of Computing Science.
    Holzapfel, André
    KTH Royal Institute of Technology.
    Marusic, Ana
    University of Split School of Medicine.
    Razmetaeva, Yulia
    Uppsala University.
    Tucker, Jason
    Malmö University, Faculty of Culture and Society (KS), Department of Global Political Studies (GPS).
    On the importance of AI research beyond disciplines: establishing guidelines2024Report (Other academic)
    Abstract [en]

    Artificial intelligence (AI) has evolved into a prominent player in various academic disciplines, transforming research approaches and knowledge generation. This paper explores the growing influence of AI across diverse fields and advocates for meaningful interdisciplinary AI research. It introduces the concept of "agonistic-antagonistic" interdisciplinary research, emphasizing a departure from conventional bridge-building approaches. Motivated by the need to address complex societal challenges, the paper calls for novel evaluation mechanisms that prioritize societal impact over traditional academic metrics. It stresses the importance of collaboration, challenging current systems that prioritize competition and individual excellence. The paper offers guiding principles for creating collaborative and co-productive interdisciplinary AI research environments, welcoming researchers to engage in discussions and contribute to the future of interdisciplinary AI research.

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  • 15. Dutoit, T.
    et al.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Jottrand, M.
    Moinet, A.
    Perez, J.
    Stylianou, Y.
    Towards a voice conversion system based on frame selection2007In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE Press, 2007, Vol. IV, p. 513-516Conference paper (Refereed)
    Abstract [en]

    The subject of this paper is the conversion of a given speaker's voice (the source speaker) into another identified voice (the target one). We assume we have at our disposal a large amount of speech samples from source and target voice with at least a part of them being parallel. The proposed system is built on a mapping function between source and target spectral envelopes followed by a frame selection algorithm to produce final spectral envelopes. Converted speech is produced by a basic LP analysis of the source and LP synthesis using the converted spectral envelopes. We compared three types of conversion: without mapping, with mapping and using the excitation of the source speaker and finally with mapping using the excitation of the target. Results show that the combination of mapping and frame selection provide the best results, and underline the interest to work on methods to convert the LP excitation.

  • 16.
    Dzhambazov, Georgi
    et al.
    Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Srinivasamurthy, Ajay
    Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain.
    Serra, Xavier
    Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain.
    Metrical-accent Aware Vocal Onset Detection in Polyphonic Audio2017In: Proceedings of the 18th International Society for Music Information Retrieval Conference, ISMIR 2017, International Society for Music Information Retrieval , 2017Conference paper (Refereed)
    Abstract [en]

    The goal of this study is the automatic detection of onsets of the singing voice in polyphonic audio recordings. Starting with a hypothesis that the knowledge of the current position in a metrical cycle (i.e. metrical accent) can improve the accuracy of vocal note onset detection, we propose a novel probabilistic model to jointly track beats and vocal note onsets. The proposed model extends a state of the art model for beat and meter tracking, in which a-priori probability of a note at a specific metrical accent interacts with the probability of observing a vocal note onset. We carry out an evaluation on a varied collection of multi-instrument datasets from two music traditions (English popular music and Turkish makam) with different types of metrical cycles and singing styles. Results confirm that the proposed model reasonably improves vocal note onset detection accuracy compared to a baseline model that does not take metrical position into account.

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  • 17.
    Falkenberg, Kjetil
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Bresin, Roberto
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Pauletto, Sandra
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Musikkommunikation och ljudinteraktion2021In: Introduktion till medieteknik / [ed] Pernilla Falkenberg Josefsson, Mikael Wiberg, Lund: Studentlitteratur AB, 2021, p. 155-166Chapter in book (Refereed)
  • 18.
    Falkenberg, Kjetil
    et al.
    Royal College of Music in Stockholm. KTH.
    Bresin, Roberto
    KTH.
    Holzapfel, Andre
    KTH.
    Pauletto, Sandra
    KTH.
    Gulz, Torbjörn
    Royal College of Music in Stockholm, Department of Jazz. KTH.
    Lindetorp, Hans
    Royal College of Music in Stockholm, Department of Music and Media Production. KTH.
    Misgeld, Olof
    Royal College of Music in Stockholm, Department of Folk Music. KTH.
    Mattias, Sköld
    Royal College of Music in Stockholm, Department of Folk Music. Royal College of Music in Stockholm, Department of Composition and Conducting. KTH.
    Student involvement in sound and music computing research: Current practices at KTH and KMH2019In: Combined proceedings of the Nordic Sound and Music Computing Conference 2019 and the Interactive Sonification Workshop 2019, 2019, p. 36-42Conference paper (Refereed)
    Abstract [en]

    To engage students in and beyond course activities has been a working practice both at KTH Sound and Music Computing group and at KMH Royal College of Music since many years. This paper collects experiences of involving students in research conducted within the two institutions.  We describe how students attending our courses are given the possibility to be involved in our research activities, and we argue that their involvement both contributes to develop new research and benefits the students in the short and long term.  Among the assignments, activities, and tasks we offer in our education programs are pilot experiments, prototype development, public exhibitions, performing, composing, data collection, analysis challenges, and bachelor and master thesis projects that lead to academic publications.

  • 19. Fossum, Dave
    et al.
    Holzapfel, André
    Bogazici University, Istanbul.
    Exploring the Music of Two Masters of the Turkmen Dutar Through Timing Analysis2014In: Proceedings of the 4th Workshop on Folk Music Analysis, Bogaziçi University , 2014, p. 52-56Conference paper (Refereed)
    Abstract [en]

    In this paper, we analyze onset characteristics to try to identify important differences between two famous Turkmen dutar performers in terms of patterns of timing. We first analyzed annotated onset data for equivalent excerpts from recordings by these two musicians. We then analyzed unannotated onset data for a larger set of entire recordings. These analyses showed several conclusions. First, during introductory strumming outside the context of a composed melody, the two have different timing habits. Mylly aga is more consistent and Purli aga more varied ¨ in terms of recurring inter-onset-intervals (IOIs). Second, during through-composed melodies, the timing profiles of the two musicians are very similar. This perhaps reflects the traditional Turkmen emphasis on preserving the form of traditional compositions in great detail and the attention paid to strumming technique. Finally, we found that automatically derived representations of rhythmic patterns, referred to as pulsation matrices, could be useful for identifying departures from typical timing patterns, which we could then analyze in order to understand such variations and their possible significance

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  • 20.
    Gedik, Ali Cenk
    et al.
    Department of Musicology, Dokuz Eylül University.
    Holzapfel, André
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    The Meaning of Music in Ethnomusicology and Music Information Retrieval: Obstacles Against Computational Ethnomusicology2018Conference paper (Refereed)
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  • 21.
    Gulz, Torbjörn
    et al.
    Royal College of Music in Stockholm, Sweden.
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Friberg, Anders
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.
    Developing a Method for Identifying Improvisation Strategies in Jazz Duos2019In: Proc. of the 14th International Symposium on CMMR / [ed] M. Aramaki, O. Derrien, R. Kronland-Martinet, S. Ystad, Marseille Cedex, 2019, p. 482-489Conference paper (Refereed)
    Abstract [en]

    The primary purpose of this paper is to describe a method to investigate the communication process between musicians performing improvisation in jazz. This method was applied in a first case study. The paper contributes to jazz improvisation theory towards embracing more artistic expressions and choices made in real life musical situations. In jazz, applied improvisation theory usually consists of scale and harmony studies within quantized rhythmic patterns. The ensembles in the study were duos performed by the author at the piano and horn players (trumpet, alto saxophone, clarinet and trombone). Recording sessions involving the ensembles were conducted. The recording was transcribed using software and the produced score together with the audio recording was used when conducting in-depth interviews, to identify the horn player’s underlying musical strategies. The strategies were coded according to previous research.

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  • 22.
    Gulz, Torbjörn
    et al.
    Royal College of Music in Stockholm, Department of Jazz.
    Holzapfel, André
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Människocentrerad teknologi, Medieteknik och interaktionsdesign, MID. (Sound and Music Computing)..
    Synchronization in a jazz trio during Accelerando and Ritardando.2021Conference paper (Refereed)
    Abstract [en]

    Background

    A prevalent feature of Jazz performance is the maintenance of an intended constant tempo [1]. Whereas an increase in tempo may be valued as a means to increase the intensity, a decrease in tempo is a widely despised practice. Sometimes, however, a jazz group deliberately wants to change the tempo, such as during the piano solo in the song ’No blues’ with the Miles Davies Quintet [2]. Changing the tempo deliberately together as a band has been documented to be a challenging task [3]. Schulze et al. [4] presented two different working models used to understand how musicians relate to change of tempo where the timekeeper continuously is working with error corrections to adjust to some predetermined value of tempo.

    Aim

    This study investigates how well three different professional double-bass players were able to synchronize to a drummer whose performance involves continuous tempo changes. According to Hofmann et al., the tempo is mainly controlled by the timing of the drummers [5]. Our main aim is to gain first insights into the differences in synchronization for accelerando, stable tempo, and ritardando.

    Method

    The setting was a trio with piano, bass, and drums. The drummer listened to a pre-recorded click track (quarter notes), and the other musicians followed his playing. The recorded music was five choruses of minor blues, where the pre-recorded click specified the tempo. All performances were played in 4/4, started at tempo 100 bpm, then accelerated linearly during two choruses to 200 bpm, remained at this tempo one chorus, and ultimately slowed down (ritardando), during two choruses to 100 bpm. Three different takes were made in a row, and all instruments were recorded on separate tracks. The note onsets of the double bass and drums were manually annotated using Sonic Visualiser, and the differences between the click and onsets were calculated. As a reference, the note onsets in a blues with a constant tempo were also recorded and analyzed. Although the bass player only related to the drummer’s interpretation of the tempo, the analysis of onset differences was conducted for the relation metronome-drums and metronome-bass. The pianist was mainly included in the study to result in an ecologically valid performance setting.

    Results

    The results show a clear positive time difference (note onsets are after the metronome) during the accelerando and a negative time difference during the ritardando for both drummer and bassist due to the musician’s aim for error correction. During the chorus with a constant tempo, the discrepancies decreased and quickly resembled the reference steady-recording discrepancies. It is also clear that the musicians play closer to the click during an increase in tempo than during a decrease.

    Discussion

    Although the purpose was to make an ecologically valid recording, the musicians reported it intricate playing to pre-recorded clicks. When annotating published commercial recordings, it is obvious that accelerando and ritardando are often performed step by step rather than in a continuous, linear fashion.

    REFERENCES

    [1] B. C. Wesolowski, “Timing deviations in jazz performance: The relationships of selected musical variables on horizontal and vertical timing relations.” Psychology of Music 2016, Vol. 44, 2016, p. 75 –94.

    [2] M. Davies, “Live At The Plugged Nickel.” Columbia -CXK 66955, 1965.

    [3] B. Givan, “Rethinking interaction in jazz improvisation,” Music Theory Online, vol. 22, no. 3, 2016.

    [4] H.-H. Schulze, A. Cordes, and D. Vorberg, “Keeping synchrony while tempo changes: Accelerando and ritardando,” Music Perception, vol. 22, no. 3, pp. 461– 477, 2005.

    [5] A. Hofmann, B. C. Wesolowski, and W. Goebl, “The Tight-interlocked Rhythm Section: Production and Perception of Synchronisation in Jazz Trio Performance.” Journal of New Music Research, 2017, pp. 1–13.

  • 23. Hagleitner, Michael
    et al.
    Holzapfel, AndréKTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Music on Crete: Traditions of a Mediterranean Island2017Collection (editor) (Other academic)
  • 24.
    Hansen, Kjetil Falkenberg
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Bresin, Roberto
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Pauletto, Sandra
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Gulz, Torbjörn
    KMH Royal College of Music in Stockholm.
    Lindetorp, Hans
    KMH Royal College of Music in Stockholm.
    Misgeld, Olof
    KMH Royal College of Music in Stockholm.
    Mattias, Sköld
    KMH Royal College of Music in Stockholm.
    Student involvement in sound and music computing research: Current practices at KTH and KMH2019In: Combined proceedings of the Nordic Sound and Music Computing Conference 2019 and the Interactive Sonification Workshop 2019, Stockholm, 2019, p. 36-42Conference paper (Refereed)
    Abstract [en]

    To engage students in and beyond course activities has been a working practice both at KTH Sound and Music Computing group and at KMH Royal College of Music since many years. This paper collects experiences of involving students in research conducted within the two institutions. 

    We describe how students attending our courses are given the possibility to be involved in our research activities, and we argue that their involvement both contributes to develop new research and benefits the students in the short and long term.  Among the assignments, activities, and tasks we offer in our education programs are pilot experiments, prototype development, public exhibitions, performing, composing, data collection, analysis challenges, and bachelor and master thesis projects that lead to academic publications.

  • 25.
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    From Dusk till dawn: An analysis of Cretan music festivities2022In: Trends in World Music Analysis: New Directions in World Music Analysis / [ed] Lawrence Beaumont Shuster, Somangshu Mukherji and Noé Dinnerstein, Routledge, 2022Chapter in book (Refereed)
  • 26.
    Holzapfel, Andre
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Introducing Political Ecology of Creative-Ai2023In: Handbook of Critical Studies of Artificial Intelligence / [ed] Simon Lindgren, Cheltenham, United Kingdom: Edward Elgar Publishing, 2023Chapter in book (Refereed)
    Abstract [en]

    This chapter introduces the perspective of political ecology to the application of artificial intelligence to artistic processes (Creative-Ai). Hence, the environmental and social impact of the development and employment of Creative-Ai are the focus of this text, when we consider them as part of an economic system that transforms artistic creation to a commodity. I first analyse specific Creative-Ai cases, and then conduct a speculation that takes Jacques Attali’s writing on the role of music in society as a vantage point, and investigates the environmental and social consequences of an automatic composition network controlled by a large music streaming platform. Whereas the possibilities that emerge from Creative-Ai may be promising from an artistic perspective, its entanglement with corporate interest raises severe concerns. These concerns can only be addressed by a wide cross-sectoral alliance between research and arts that develops a critical perspective on the future directions of Creative-Ai.

  • 27.
    Holzapfel, Andre
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Benetos, Emmanouil
    Automatic music transcription and ethnomusicology: A user study2019In: Proceedings of the 20th International Society for Music Information Retrieval Conference, ISMIR 2019, 2019, p. 678-684Conference paper (Refereed)
    Abstract [en]

    Converting an acoustic music signal into music notation using a computer program has been at the forefront of music information research for several decades, as a task referred to as automatic music transcription (AMT). However, current AMT research is still constrained to system development followed by quantitative evaluations; it is still unclear whether the performance of AMT methods is considered sufficient to be used in the everyday practice of music scholars. In this paper, we propose and carry out a user study on evaluating the usefulness of automatic music transcription in the context of ethnomusicology. As part of the study, we recruited 16 participants who were asked to transcribe short musical excerpts either from scratch or using the output of an AMT system as a basis. We collect and analyze quantitative measures such as transcription time and effort, and a range of qualitative feedback from study participants, which includes user needs, criticisms of AMT technologies, and links between perceptual and quantitative evaluations on AMT outputs. The results show no quantitative advantage of using AMT, but important indications regarding appropriate user groups and evaluation measures are provided.

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  • 28.
    Holzapfel, Andre
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Benetos, Emmanouil
    School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK.
    Killick, Andrew
    Department of Music, University of Sheffield, Sheffield, UK.
    Widdess, Richard
    Department of Music, SOAS University of London, UK.
    Humanities and engineering perspectives on music transcription2021In: Digital Scholarship in the Humanities, ISSN 2055-7671, E-ISSN 2055-768XArticle in journal (Refereed)
    Abstract [en]

    Music transcription is a process of creating a notation of musical sounds. It has been used as a basis for the analysis of music from a wide variety of cultures. Recent decades have seen an increasing amount of engineering research within the field of Music Information Retrieval that aims at automatically obtaining music transcriptions in Western staff notation. However, such approaches are not widely applied in research in ethnomusicology. This article aims to bridge interdisciplinary gaps by identifying aspects of proximity and divergence between the two fields. As part of our study, we collected manual transcriptions of traditional dance tune recordings by eighteen transcribers. Our method employs a combination of expert and computational evaluation of these transcriptions. This enables us to investigate the limitations of automatic music transcription (AMT) methods and computational transcription metrics that have been proposed for their evaluation. Based on these findings, we discuss promising avenues to make AMT more useful for studies in the Humanities. These are, first, assessing the quality of a transcription based on an analytic purpose; secondly, developing AMT approaches that are able to learn conventions concerning the transcription of a specific style; thirdly, a focus on novice transcribers as users of AMT systems; and, finally, considering target notation systems different from Western staff notation.

  • 29.
    Holzapfel, Andre
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Hagleitner, Michael
    Stella, Pashalidou
    Diversity of Traditional Dance Expression in Crete: Data Collection, Research Questions, and Method Development2020Conference paper (Refereed)
  • 30.
    Holzapfel, Andre
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Jääskeläinen, Petra
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Kaila, Anna-Kaisa
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Environmental and Social Sustainability of Creative-Ai2022Conference paper (Other academic)
    Abstract [en]

    The recent developments of artificial intelligence increase its capability for a creation of arts in both largely autonomous and collaborative contexts. In both contexts, Ai aims to imitate, combine, and extend existing artistic styles, and can transform creative practices. In our ongoing research, we investigate such Creative-Ai from sustainability and ethical perspectives. The two main focus areas are understanding the environmental sustainability aspects (material, practices) in the context of artistic processes that involve Creative-Ai, and ethical issues related to who gets to be involved in the creation process (power, authorship, ownership). This paper provides an outline of our ongoing research in these two directions. We will present our interdisciplinary approach, which combines interviews, work- shops, online ethnography, and energy measurements, to address our research questions: How is Creative-Ai currently used by artist communities, and which future applications do artists imagine? When Ai is applied to creating art, how might it impact the economy and environment? And, how can answers to these questions guide requirements for intellectual property regimes for Creative-Ai?

  • 31.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    A case study of ethnography and computational analysis as complementary tools for analyzing dance tunes2018Conference paper (Refereed)
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  • 32.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    A corpus study on rhythmic modes in Turkish makam music and their interaction with meter2015In: Proceedings of the 15. Congress of the Society for Music Theory, 2015Conference paper (Refereed)
  • 33.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Computational Analysis of Melodic Motives in Cretan Leaping Dances: Motivations, Perspectives, and Limitations2015Conference paper (Other academic)
  • 34.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Die ersten Schritte: Interviews mit kretischen Tanzlehrern2017In: Music on Crete: Traditions of a Mediterranean island / [ed] Michael Hagleitner and Andre Holzapfel, Vienna: Institut fuer Musikwissenschaft, Universität Wien , 2017, p. 303-330Chapter in book (Other academic)
  • 35.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Leaping dances in Crete: Tradition in motion2014Conference paper (Refereed)
    Abstract [en]

    Throughout the last decades a new enthusiasm for local music and an increasing trend towards rediscovering old local dances and tunes gained momentum in the island of Crete. In the presented analysis I combine an ethnographic with a comparative approach, driven by audio signal analysis tools, in order to address the question of how far tunes that serve to define local and micro-local identities differ in certain aspects with regard to the sound of performances. For this I investigate three sound aspects of Cretan leaping dance performances: tempo, rhythmic stress patterns, and contained melodic patterns. I accompany the analytical results with information obtained from my interviews with dancing teachers and musicians. My results depict small but significant differences depending on the dance, but also underline the great homogeneity of the repertoire. The results imply that all three aspects contribute to the fine differences between the dance tunes, with a clear emphasis on the melodic phrases. Therefore, this study with its findings and its computational tools paves the way towards the establishment of dictionaries of characteristic melodic phrases of Cretan dance repertoire, as well as of dance tunes with similar morphology.

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  • 36.
    Holzapfel, André
    Bogazici University.
    Melodic key phrases in traditional Cretan dance tunes2015In: Proceedings of the 5th International Workshop on Folk Music Analysis, Institut Jean le Rond d'Alembert , 2015, p. 79-82Conference paper (Refereed)
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  • 37.
    Holzapfel, André
    Bogaziçi University, Turkey.
    Relation between surface rhythm and rhythmic modes in Turkish makam music2015In: Journal of New Music Research, ISSN 0929-8215, E-ISSN 1744-5027, Vol. 44, no 1, p. 25-38Article in journal (Refereed)
    Abstract [en]

    Sounds in a piece of music form rhythmic patterns on the surface of a music signal, and in a metered piece these patterns stand in some relation to the underlying rhythmic mode or meter. In this paper, we investigate how the surface rhythm is related to the usul, which are the rhythmic modes in compositions of Turkish makam music. On a large corpus of notations of vocal pieces in short usul we observe the ways notes are distributed in relation to the usul. We observe differences in these distributions between Turkish makam and Eurogenetic music, which imply a less accentuated stratification of meter in Turkish makam music. We observe changes in rhythmic style between two composers who represent two different historical periods in Turkish makam music, a result that adds to previous observations on changes in style of Turkish makam music throughout the centuries. We demonstrate that rhythmic aspects in Turkish makam music can be considered as the outcome of a generative model, and conduct style comparisons in a Bayesian statistical framework.

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  • 38.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Rhythmic and melodic aspects of Cretan Leaping dances2017In: Music on Crete: Traditions of a Mediterranean island / [ed] Michael Hagleitner and Andre Holzapfel, Vienna: Institut fuer Musikwissenschaft, Universität Wien , 2017, p. 281-302Chapter in book (Other academic)
  • 39.
    Holzapfel, André
    Istanbul Technical University.
    STRUCTURE AND INTERACTION IN CRETAN LEAPING DANCES: CONNECTING ETHNOGRAPHY AND COMPUTATIONAL ANALYSIS2018Doctoral thesis, monograph (Other academic)
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  • 40.
    Holzapfel, André
    Bogazici University, Turkey.
    TEMPO AND PROSODY IN TURKISH TAKSIM IMPROVISATION2013In: Proceedings of the 3rd Workshop on Folk Music Analysis, Meertens Institute; Department of Information and Computing Sciences, Utrecht University , 2013, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Instrumental improvisation in Turkish makam music, the taksim, is considered to be free-rhythm, that is its rhythm develops without the underlying template of a meter or continuous organized pulsation. In this paper, we want to examine how in this setting, rhythmic idioms are formed and maintained throughout a performance. For this, we will apply a simple signal processing approach. We show differences that can be observed between performers, and raise the question if a tempo could be evoked by certain regularities in the occurring rhythmic elaborations.

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  • 41.
    Holzapfel, André
    et al.
    Austrian Research Institute for Artificial Intelligence (OFAI).
    Benetos, Emmanouil
    The Sousta corpus: Beat-informed automatic transcription of traditional dance tunes2016In: Proceedings of ISMIR - International Conference on Music Information Retrieval, 2016, p. 531-537Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a new corpus for research in computational ethnomusicology and automatic music transcription, consisting of traditional dance tunes from Crete. This rich dataset includes audio recordings, scores transcribed by ethnomusicologists and aligned to the audio performances, and meter annotations. A second contribution of this paper is the creation of an automatic music transcription system able to support the detection of multiple pitches produced by lyra (a bowed string instrument). Furthermore, the transcription system is able to cope with deviations from standard tuning, and provides temporally quantized notes by combining the output of the multi-pitch detection stage with a state-of-the-art meter tracking algorithm. Experiments carried out for note tracking using 25ms onset tolerance reach 41.1% using information from the multi-pitch detection stage only, 54.6% when integrating beat information, and 57.9% when also supporting tuning estimation. The produced meter aligned transcriptions can be used to generate staff notation, a fact that increases the value of the system for studies in ethnomusicologyIn this paper, we present a new corpus for research in computational ethnomusicology and automatic music transcription, consisting of traditional dance tunes from Crete. This rich dataset includes audio recordings, scores transcribed by ethnomusicologists and aligned to the audio performances, and meter annotations. A second contribution of this paper is the creation of an automatic music transcription system able to support the detection of multiple pitches produced by lyra (a bowed string instrument). Furthermore, the transcription system is able to cope with deviations from standard tuning, and provides temporally quantized notes by combining the output of the multi-pitch detection stage with a state-of-the-art meter tracking algorithm. Experiments carried out for note tracking using 25ms onset tolerance reach 41.1% using information from the multi-pitch detection stage only, 54.6% when integrating beat information, and 57.9% when also supporting tuning estimation. The produced meter aligned transcriptions can be used to generate staff notation, a fact that increases the value of the system for studies in ethnomusicology

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  • 42.
    Holzapfel, André
    et al.
    Universitat Pompeu Fabra Barcelona, Spain.
    Bozkurt, Baris
    Metrical Strength and Contradiction in Turkish Makam Music2012In: Proceedings of the 2nd CompMusic Workshop, 2012, p. 79-84Conference paper (Other academic)
    Abstract [en]

    In this paper we investigate how note onsets in Turkish Makam music compositions are distributed, and in how far this distribution supports or contradicts the metrical structure of the pieces, the usul. We use MIDI data to derive the distributions in the form of onset histograms, and compare them with metrical weights that are applied to describe the usul in theory. We compute correlation and syncopation values to estimate the degrees of support and contradiction, respectively. While the concept of syncopation is rarely mentioned in the context of this music, we can gain interesting insight into the structure of a piece using such a measure. We show that metrical contradiction is systematically applied in some metrical structures. We will compare the differences between Western music and Turkish Makam music regarding metrical support and contradiction. Such a study can help avoiding pitfalls in later attempts to perform audio processing tasks such as beat tracking or rhythmic similarity measurements.

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  • 43.
    Holzapfel, André
    et al.
    Universitat Pompeu Fabra, Spain .
    Davies, Matthew E. P.
    Zapata, José R.
    Oliveira, Joao Lobato
    Gouyon, Fabien
    Selective sampling for beat tracking evaluation2012In: IEEE Transactions on Audio, Speech, and Language Processing, ISSN 1558-7916, E-ISSN 1558-7924, Vol. 20, no 9, p. 2539-2548Article in journal (Refereed)
    Abstract [en]

    In this paper, we propose a method that can identify challenging music samples for beat tracking without ground truth. Our method, motivated by the machine learning method "selective sampling," is based on the measurement of mutual agreement between beat sequences. In calculating this mutual agreement we show the critical influence of different evaluation measures. Using our approach we demonstrate how to compile a new evaluation dataset comprised of difficult excerpts for beat tracking and examine this difficulty in the context of perceptual and musical properties. Based on tag analysis we indicate the musical properties where future advances in beat tracking research would be most profitable and where beat tracking is too difficult to be attempted. Finally, we demonstrate how our mutual agreement method can be used to improve beat tracking accuracy on large music collections.

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  • 44.
    Holzapfel, André
    et al.
    Sound and Music Computing Group, INESC TEC, Porto, Portugal.
    Davies, Matthew
    Zapata, Jose Ricardo
    Oliveira, Joao Lobato
    Gouyon, Fabien
    On the automatic identification of difficult examples for beat tracking: towards building new evaluation datasets2012In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE conference proceedings, 2012, p. 89-92Conference paper (Refereed)
    Abstract [en]

    In this paper, an approach is presented that identifies music samples which are difficult for current state-of-the-art beat trackers. In order to estimate this difficulty even for examples without ground truth, a method motivated by selective sampling is applied. This method assigns a degree of difficulty to a sample based on the mutual disagreement between the output of various beat tracking systems. On a large beat annotated dataset we show that this mutual agreement is correlated with the mean performance of the beat trackers evaluated against the ground truth, and hence can be used to identify difficult examples by predicting poor beat tracking performance. Towards the aim of advancing future beat tracking systems, we demonstrate how our method can be used to form new datasets containing a high proportion of challenging music examples.

  • 45.
    Holzapfel, André
    et al.
    Austrian Research Institute for Artificial Intelligence (OFAI).
    Flexer, Arthur
    Widmer, Gerhard
    Improving tempo-sensitive and tempo-robust descriptors for rhythmic similarity2011In: Proceedings of the Conference on Sound and Music Computing (SMC), Sound and music Computing network , 2011Conference paper (Refereed)
    Abstract [en]

    For the description of rhythmic content of music signals usually features are preferred that are invariant in presence of tempo changes. In this paper it is shown that the importance oftempo depends on the musical context. For popular music, a tempo-sensitive feature is improved on multiple datasets using analysis of variance, and it is shown that also a tempo-robust description profits from the integration into the resulting processing framework. Important insights are given into optimal parameters for rhythm description, and limitations of current approaches are indicated.

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  • 46.
    Holzapfel, André
    et al.
    Austrian Research Institute for Artificial Intelligence (OFAI).
    Grill, Thomas
    Bayesian meter tracking on learned signal representations2016In: Proceedings of ISMIR - International Conference on Music Information Retrieval, ISMIR , 2016, p. 262-268Conference paper (Refereed)
    Abstract [en]

    Most music exhibits a pulsating temporal structure, known as meter. Consequently, the task of meter tracking is of great importance for the domain of Music Information Retrieval. In our contribution, we specifically focus on Indian art musics, where meter is conceptualized at several hierarchical levels, and a diverse variety of metrical hierarchies exist, which poses a challenge for state of the art analysis methods. To this end, for the first time, we combine Convolutional Neural Networks (CNN), allowing to transcend manually tailored signal representations, with subsequent Dynamic Bayesian Tracking (BT), modeling the recurrent metrical structure in music. Our approach estimates meter structures simultaneously at two metrical levels. The results constitute a clear advance in meter tracking performance for Indian art music, and we also demonstrate that these results generalize to a set of Ballroom dances. Furthermore, the incorporation of neural network output allows a computationally efficient inference. We expect the combination of learned signal representations through CNNs and higher-level temporal modeling to be applicable to all styles of metered music, provided the availability of sufficient training data.

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  • 47.
    Holzapfel, André
    et al.
    New York University Abu Dhabi.
    Krebs, Florian
    Srinivasamurthy, Ajay
    Tracking the “odd”: Meter inference in a culturally diverse music corpus2014In: Proceedings of ISMIR - International Conference on Music Information Retrieval, ISMIR , 2014, p. 425-430Conference paper (Refereed)
    Abstract [en]

    In this paper, we approach the tasks of beat tracking, downbeat recognition and rhythmic style classification in nonWestern music. Our approach is based on a Bayesian model, which infers tempo, downbeats and rhythmic style, from an audio signal. The model can be automatically adapted to rhythmic styles and time signatures. For evaluation, we compiled and annotated a music corpus consisting of eight rhythmic styles from three cultures, containing a variety of meter types. We demonstrate that by adapting the model to specific styles, we can track beats and downbeats in odd meter types like 9/8 or 7/8 with an accuracy significantly improved over the state of the art. Even if the rhythmic style is not known in advance, a unified model is able to recognize the meter and track the beat with comparable results, providing a novel method for inferring the metrical structure in culturally diverse datasets.

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  • 48.
    Holzapfel, André
    et al.
    Bogazici University, Turkey.
    Simsekli, Umut
    Sentürk, Sertan
    Cemgil, Ali Taylan
    Section-level modeling of musical audio for linking performances to scores in Turkish makam music2015In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE conference proceedings, 2015, p. 141-145Conference paper (Refereed)
    Abstract [en]

    Section linking aims at relating structural units in the notation of a piece of music to their occurrences in a performance of the piece. In this paper, we address this task by presenting a score-informed hierarchical Hidden Markov Model (HHMM) for modeling musical audio signals on the temporal level of sections present in a composition, where the main idea is to explicitly model the long range and hierarchical structure of music signals. So far, approaches based on HHMM or similar methods were mainly developed for a note-to-note alignment, i.e. an alignment based on shorter temporal units than sections. Such approaches, however, are conceptually problematic when the performances differ substantially from the reference score due to interpretation and improvisation, a very common phenomenon, for instance, in Turkish makam music. In addition to having low computational complexity compared to note-to-note alignment and achieving a transparent and elegant model, the experimental results show that our method outperforms a previously presented approach on a Turkish makam music corpus.

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  • 49.
    Holzapfel, André
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Sturm, Bob
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.
    Coeckelbergh, Mark
    Department of Philosophy, University of Vienna, Vienna, Austria.
    Ethical Dimensions of Music Information Retrieval Technology2018In: Transactions of the International Society for Music Information Retrieval, E-ISSN 2514-3298, Vol. 1, no 1, p. 44-55Article in journal (Refereed)
    Abstract [en]

    This article examines ethical dimensions of Music Information Retrieval (MIR) technology.  It uses practical ethics (especially computer ethics and engineering ethics) and socio-technical approaches to provide a theoretical basis that can inform discussions of ethics in MIR. To help ground the discussion, the article engages with concrete examples and discourse drawn from the MIR field. This article argues that MIR technology is not value-neutral but is influenced by design choices, and so has unintended and ethically relevant implications. These can be invisible unless one considers how the technology relates to wider society. The article points to the blurring of boundaries between music and technology, and frames music as “informationally enriched” and as a “total social fact.” The article calls attention to biases that are introduced by algorithms and data used for MIR technology, cultural issues related to copyright, and ethical problems in MIR as a scientific practice. The article concludes with tentative ethical guidelines for MIR developers, and calls for addressing key ethical problems with MIR technology and practice, especially those related to forms of bias and the remoteness of the technology development from end users.

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  • 50.
    Holzapfel, André
    et al.
    University of Crete.
    Stylianou, Yannis
    A scale transform based method for rhythmic similarity of music2009In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE conference proceedings, 2009, p. 317-320Conference paper (Refereed)
    Abstract [en]

    This paper introduces scale transforms to measure rhythmic similarity between two musical pieces. The rhythm of a piece of music is described by the scale transform magnitude, computed by transforming the sample autocorrelation of its onset strength signal to the scale domain. Then, two pieces can be compared without the impact of tempo differences by using simple distances between these descriptors like the cosine distance. A widely used dance music dataset has been chosen for proof of concept. On this data set, the proposed method based on scale transform achieves classification results as high as other state of the art approaches. On a second data set, which is characterized by much larger intra-class tempo variance, the scale transform based measure improves classification compared to previously presented measures by 41%.

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