• Home
• About Us
• Events
• Archive
• Subscribe
• Contact

Linking Expectation and Emotion in a Live Concert Experiment
Hauke Egermann
McGill University
Abstract/Bio

Abstract
In the presented study, the often theorized role of musical expectations in inducing listener's emotions will be investigated. Therefore the talk will present results from a live flute concert experiment with 50 participants. To confirm the existence of the link between expectation and emotion, a three-fold approach was undertaken: (1) Based on an information theoretic model, musical expectancies were predicted by analyzing the musical stimuli used. (2) A continuous expectation rating scale was used to measure the subjective unexpectedness of the music heard. (3) Finally, emotions were also measured using a multi-component measurement approach (subjective feeling, expressive behavior and peripheral arousal). A causal relationship will be predicted between the violation of musical expectations and emotional reactions. Thus, musical structures leading to expectation reactions are also thought to be manifested in emotional reactions at different emotion component levels.

The Effects of Polyrhythm Complexity and Stream Segregation on Polyrhythm Tracking in Musicians
Bruno Repp, Haskins Laboratories
Ève Poudrier and Brian Fidali, Yale University
Abstract/Bio

Abstract
Previous research on polyrhythms has focused on beat-induction tasks using relatively simple polyrhythm configurations. We hope to better understand attentional limitations on musicians' processing of more complicated polyrhythms. Using the work of Jones et al. (1995) as a starting point, we have employed an error-detection task to track attentional flexibility. Polyrhythm configurations of varying complexity were chosen as stimuli. Additionally, we have manipulated pitch separation between the polyrhythmic pulse streams in order to encourage selective or integrated attending. Our results will be explained briefly in the context of music cognition research and the field of music theory.

Bios
Bruno Repp is a Senior Research Scientist at Haskins Laboratories, where his numerous studies focus on music perception and action.

Ève Poudrier is a Professor at the Yale Department of Music. Her research focuses primarily on issues of perception and cognition of musical rhythm and polymeter.

Brian Fidali is a senior at Yale College, where he will complete the Intensive Music Major this May.

Effects of Single-Onset Insertions and Deletions on Perceived Rhythmic Similarity
Olaf Post and Godfried Toussaint
Harvard University
Abstract/Bio

Abstract
The 'edit distance' is a measure of similarity between two rhythms. It is defined as the lowest number of operations (insertions, deletions, and substitutions) on the smallest time units that are required to transform one rhythm into the other. This distance measure has been used frequently in music information retrieval applications, as it is suggested to make good predictions of rhythmic similarity as judged by human listeners (Toussaint et al., 2010). In this experiment, we test the predictive value of the edit distance model specifically in the context of a highly syncopated rhythm, the clave son. Despite the degree of syncopation, the results of this experiment show a high correlation between the edit distance and the human judgments.

Bios
Olaf Post is preceptor in music at Harvard University. He holds a PhD in music theory from Columbia University, as well as master's degrees in philosophy and biotechnology. He also studied piano and composition at the Conservatory of Amsterdam, and is active as a pianist and organist. Prior to joining the Harvard faculty, Post was a research fellow in music cognition at The Ohio State University, where he worked with David Huron. His research focuses on music cognition and performance analysis. In 2010, he received a Faculty Award from the Harvard Mind, Brain, and Behavior Program to pursue research in music cognition.

Godfried T. Toussaint is presently a visiting scholar at Harvard University doing research on music cognition in the Department of Music. He is also a visiting scholar and lecturer in the Computer Science Department at Tufts University, a research affiliate in the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology, a professor emeritus at McGill University, and a researcher at the Centre for Interdisciplinary Research in Music Media and Technology, also at McGill University. His main research interests lie in the areas of computational geometry, information theory, pattern recognition, instance-based learning, music information retrieval, and computational music theory. He is a founder of several annual conferences and workshops, an editor of several journals, has received numerous awards, and has published more than 360 papers in these areas. In 2009 he was awarded a Radcliffe Fellowship by the Radcliffe Institute for Advanced Study at Harvard University for the 2009-1010 academic year.

An Exploration of the Temporal Dynamics of Music Processing Using Gap Insertion
Morwaread Farbood, New York University
Jess Rowland, New York University
Oded Ghitza, Boston University
David Poeppel, New York University
Abstract/Bio

Abstract
We present a study that examines the question of natural timescales for perceptual analysis and the relationship between these timescales for music and language. Previous research on speech has indicated an oscillatory mechanism on a specific timescale. This experiment addresses whether the perception of musical structure, in the form of key perception, is subject to a similar principle.

Timbre Spaces as Models for Analysis and Composition of Complex Sounds
Aaron Einbond
Columbia University
Abstract/Bio

Abstract
How can sound descriptors arising from studies in music perception be applied to inform composition and analysis? Perceptual research by Wessel and Grey suggests timbre can be organized by listeners into a multi-dimensional spatial representation. Building on this work, we propose an approach to timbre that is based on computer analysis of perceptually-relevant descriptors. Using the recent concept of corpus-based concatenative synthesis (CBCS), a database of samples is plotted in a spatial representation corresponding to any two, three, or more of these descriptors. A musical phrase may be generated by drawing a curve in the space or by closest matches to an external target sound file. While this technique can be used for more traditional sounds, it is especially effective for organizing non-pitched sounds based on their timbral characteristics, both in the contexts of electronic music and computer-assisted composition for acoustic instruments. This technique is implemented with the CataRT package for computer programs Max/MSP and OpenMusic.

Bio
Aaron Einbond is Mellon Postdoctoral Fellow in Music at Columbia University where his work explores the intersection of composition, computer music, music perception, field recording, and sound installation.

Flux of Upward: A Computational Model of a Textural Device in Ligeti's Late Music.
Joshua Mailman
New York University and Columbia University
Abstract/Bio

Bio
Joshua Banks Mailman (A.B., University of Chicago; M.A. and Ph.D., Eastman School of Music) teaches at New York University and Columbia University. His publications appear in Psychology of Music, Music Theory Online, and Music Analysis. His research focuses on temporal dynamic form, philosophical and computational aspects, especially for music since 1900.

On the Role of Musical Ability in Second Language Learning
L. Robert Slevc
University of Maryland, College Park
Abstract/Bio

Abstract
Musical ability predicts how well adults learn the sound system of a second language, but it is not clear what mechanisms underlie this effect. I will briefly discuss some work-in-progress that aims to determine (a) the specific kinds of linguistic advantages that are associated with musical ability, and (b) the specific type(s) of musical training (or aptitude) that benefit linguistic processing.

Music Perception and Music Theory Pedagogy: A Curriculum Based on the Principles of the Implication-Realization Model
Alexander Rozin and Mark Rimple
West Chester University
Abstract/Bio

Abstract
The traditional methods of music theory pedagogy fail to adequately prepare today's music students to be successful and sophisticated composers, performers, music teachers, and musicologists. A new, alternative curriculum based on the principles of the Implication-Realization Model addresses the needs of the contemporary musician. In particular, this curriculum and accompanying textbook:

1. focus primarily on music perception;
2. present a parametric approach to analysis in which often-neglected parameters such as texture and melody are focal topics on par with harmony;
3. explain how musical parameters generate tension and closure;
4. explore hierarchical structure in form, melody, and harmony; and
5. demonstrate the analytical approach on a plurality of musical styles.

This paper discusses the rationale of the curriculum and the overall structure of the four-semester sequence that culminates with compositional and analytical capstone projects that exemplify the potentially rich interface between music analysis, composition, performance, and perception.

Learning Tonal Representations Over Time: A Computational Approach
Kat Agres
Cornell University
Abstract/Bio

Abstract
Many computational models of music have focused on the ultimate product of the network, such as the ability to produce sophisticated compositions. Using a Simple Recurrent Network (SRN), the present research will instead focus on the means to that end. By examining the SRN's internal structure, I will explore how tonal representations are learned over a period of increasing training. In two experiments, listeners rate the SRN's novel compositions from different points along its learning trajectory. The sparseness of the network's hidden layer is then compared to the behavioral ratings of the compositions. The results provide evidence that sparseness is a mechanism that facilitates the network's ability to produce more complex and stylistic compositions over time.

Motion in Tonal Space and Emotion in Music
Marina Korsakova-Kreyn
Abstract/Bio

Abstract
Tonal modulation is one of the main structural and expressive aspects of music in the European musical tradition. Freedom of tonal modulation was achieved through the adoption of equal-tempered tuning, providing for tonal reorientation to any of the twelve chromatic steps of the scale. Modulation is an important aspect of musical syntax because it is intimately related to the closure provided by the cadence and thus to the formation of musical structures. Although tonal modulation is thought to produce strong emotional effects, these effects have not yet been thoroughly explored. We conducted two experiments to investigate affective responses to tonal modulation by using bipolar scales related to valence, synaesthesia, potency, and tension. Experiment 1 examined affective responses to modulation to all twelve major and minor keys of the Western tonal schema with controlled harmonic progressions. The results indicated dependence of affective response on degree of modulation and mode. Experiment 2 examined responses to modulations to the subdominant, the dominant, and the descending major third with the balanced set of controlled harmonic progressions and real music excerpts. These modulations were studied in the major mode only in order to provide ecological validity of the stimuli, particularly those modulating to the dominant. In addition, Experiment 2 investigated the affective influence of melodic direction in soprano and bass melodic lines. The results agreed with the theoretical model of pitch proximity based on the circle of fifths and demonstrated the influence of melodic direction and musical style on emotional response to reorientation in tonal space.

An Oral Tradition of Long-Term Pitch Memory
Ian Quinn
Yale University
Abstract/Bio

Bio
Ian Quinn is Associate Professor of Music and Cognitive Science at Yale University, and editor of the Journal of Music Theory. He is interested in mental representations of musical knowledge, particularly knowledge about pitch, melody, and harmony. His work has been published in Science, Music Theory Spectrum, Music Perception, and many other academic journals, and has been recognized by the Society for Music Theory's Emerging Scholar Award as well as its Outstanding Publication Award. He serves on the executive boards of the Society for Mathematics and Computation in Music and the Northeast Music Cognition Group. At Yale he teaches courses in music theory, music psychology, research methods, and Sacred Harp singing.

Modeling Expressive Timing in Music Performance: Some Implications for Tension Research
Panayotis Mavromatis
New York University
Abstract/Bio

Bio
Panos Mavromatis is Assistant Professor at NYU's Department of Music and Performing Arts and a member of the Music and Audio Research Laboratory (MARL). His research focuses on machine-learning analysis and computational modeling of music theory and cognition. His areas of interest include: algorithmic analysis and modeling of style in Western and non-Western musical idioms; cognitive representations of tonal and post-tonal structure; intelligent tutoring systems and the acquisition of musical skill; and more recently, expresive timing in music performance.