No abstract

No abstract

Building on the work of Leonard B. Meyer, 3 researchers commonly agree that expectations based on recent past context guide musical perception. In music applications, exactly how we make musical Research using statistical and information-theoretic tools provides inference and prediction models that, to a certain extent, can generate new musical works imitating the style of the great masters.

This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are proposed. A technique called the ACTwg employs genre-adaptive semantic computing of mood-related social tags, whereas ACTwg-SLPwg combines semantic computing and audio-based modelling, both in a genre-adaptive manner. The proposed techniques are experimentally evaluated at predicting listener ratings related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outperforms a semantic computing technique that does not exploit genre information, and ACTwg-SLPwg outperforms conventional techniques and other genre-adaptive alternatives. In particular, improvements in the prediction rates are obtained for the valence dimension which is typically the most challenging core affect dimension for audio-based annotation. The specificity of genre categories is not crucial for the performance of ACTwg-SLPwg. The study also presents analytical insights into inferring a concise tag-based genre representation for genre-adaptive music mood analysis.

This article reports a study in which listeners were asked to provide continuous ratings of perceived emotional content of clinical music therapy improvisations. Participants were presented with 20 short excerpts of music therapy improvisations, and had to rate perceived activity, pleasantness and strength using a computer-based slider interface. A total of nine musical features relating to various aspects of the music (timing, register, dynamics, tonality, pulse clarity and sensory dissonance) were extracted from the excerpts, and relationships between these features and participants' emotion ratings were investigated. The data were analysed in three stages. First, inter-dimension correlations revealed that ratings of activity and pleasantness were moderately negatively correlated, activity and strength were strongly positively correlated, and strength and pleasantness were moderately negatively correlated. Second, a series of cross-correlation analyses revealed that the temporal lag between musical features and listeners' dimension ratings differed across both variables and dimensions. Finally, a series of linear regression analyses produced significant feature prediction models for each of the three dimensions, accounting for 80 percent ( activity), 57 percent ( pleasantness ) and 84 percent ( strength) of the variance in participants' ratings. Activity was best predicted by high note density and high pulse clarity, pleasantness by low note density and high tonal clarity, and strength by high mean velocity and low note density. The results are discussed in terms of their fit with other work reported in the music psychology literature, and their relevance to clinical music therapy research and practice.

No abstract

This thesis investigates the expressive means through which musicians well versed in groove-based music shape the timing of a rhythmic event, with a focus on the interaction between produced timing and sound features. In three performance experiments with guitarists, bassists, and drummers, I tested whether musicians systematically manipulate acoustic factors such as duration, intensity, and volume when they want to play with a specific microrhythmic style (pushed, on-the-beat, or laidback).The results show that all three groups of instrumentalists indeed played pushed, on-the-beat, or laid-back relative to the reference pulse and in line with the instructed microrhythmic styles, and that there were systematic and consequential sound differences. Guitarists played backbeats with a longer duration and darker sound in relation to pushed and laid-back strokes. Bassists played pushed beats with higher intensity than on-the-beat and laid-back strokes. For the drummers, we uncovered different timing-sound combinations, including the use of longer duration (snare drum) and higher intensity (snare drum and hi-hat), to distinguish both laid-back and pushed from on-the-beat strokes. The metronome as a reference pulse led to less marked timing profiles than the use of instruments as a reference, and it led in general to earlier onset positions as well, which can perhaps be related to the phenomenon of "negative mean asynchrony." We also conducted an in-depth study of the individual drummers' onset and intensity profiles using hierarchical cluster analyses and phylogenetic tree visualizations and uncovered a diverse range of strategies.The results support the research hypothesis that both temporal and sound-related properties contribute to how we perceive the location of a rhythmic event in time. I discuss these results in light of theories and findings from other studies of the perception and performance of groove, as well as research into rhythm and microrhythmic phenomena such as perceptual centers and onset asynchrony/anisochrony. This thesis was borne of blood, sweat, and tears, as well as a whole lotta love. (Musical puns intended, though mainly for the in crowd [Oops, I did it again].)First of all, I would like to thank my supervisors, Anne Danielsen and Kristian Nymoen, for their invaluable guidance and support throughout this journey. Anne, thank you first and foremost for providing the opportunity to research groove music in a scholarly, scientific manner for all these years -the combination of praxis and theory have bolstered its awesome power for me many times over. Your shrewd mentorship, unceasing kindness and patience, and limitless passion for knowledge have been a constant source of learning and inspiration. It is an honor to work alongside such a juggernaut scholar (and fellow funk head!), and I hope to continue unraveling the mysteries of groove together with you. Kristian, thank you for painlessly leading me through a new and wonderful technological path, one that has opened up so many analytical possibil...

This article proposes an approach to the problem of automated extraction of motivic patterns in monodies. Different musical dimensions, restricted in current approaches to the most prominent melodic and rhythmic features at the surface level, are defined. The proposed strategy of detection of repeated patterns consists of an exact matching of the successive parameters forming the motives. We suggest a generalization of the multiple-viewpoint approach that allows a variability of the types of parameters (melodic, rhythmic, etc.) defining each successive extension of these motives. This enables us to take into account a more general class of motives, called heterogeneous motives, which includes interesting motives beyond the scope of previous approaches. Besides, this heterogeneous representation of motives may offer more refined explanations concerning the impact of gross contour representation in motivic analysis. This article also shows that the main problem aroused by the pattern extraction task is related to the control of the combinatorial redundancy of musical structures. Two main strategies are presented, that ensure an adaptive filtering of the redundant structures, and which are based on the notions of closed and cyclic patterns. The method is illustrated with the analysis of two pieces: a medieval Geisslerlied and a Bach Invention.