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Centre for Music and Science

 

Computational music cognition

The goal of computational music cognition research is to develop computer programs that simulate the psychological processes underpinning human musicality. This might for example include the perception of metre, the elicitation of expectation, or the evocation of beauty. Our approaches include psychoacoustic models grounded in signal processing, cognitive models grounded in symbol manipulation, and connectionist models grounded in deep learning. By developing and validating such models, we hope both to set music psychology on a rigorous mathematical foundation, and to create exciting software tools that can empower artists to create music in new ways. Current projects in this theme include: 

  • Acoustics and emotion
  • Consonance and dichotic listening
  • Consonance and timbre
  • Deep learning models of musical expectation
  • Pitch and categorical perception
  • Timing in organ performance
  • Timing in jazz ensembles
  • Tonality and emotion

Scaling up music psychology research with PsyNet

Our new software PsyNet enables music psychologists to run advanced behavioral experiments ranging from adaptive psychophysics to simulated cultural evolution. It provides many useful features for music experiments, including audio pre-screeners, stimulus generators, and online recording analysis. For more information see link.

Testing individual differences with psychTestR

Our psychTestR software has been adopted by music laboratories across the world as a tool for testing individual differences in music psychology studies. A broad range of music listening tests (e.g. melody discrimination, beat perception, tuning perception, rhythm perception) and self-report measures (e.g. Goldsmiths Musical Sophistication Index, Home Music Environment, Flow Experience, Music Engagement) have been implemented in psychTestR, as well as a large number of non-musical performance tests and psychosocial questionnaires. These form the basis of several ongoing large-scale music testing initiatives, such as the LongGold schools project and the Harvard Musical IQ project. For more information see link.

Score design for music reading: Cognitive and artistic perspectives

This project examines the cognitive processes that musicians use to read musical scores, and aims to propose new design principles to facilitate the reading of such scores. Our work so far suggests that simple but systematic and structured modifications to standard notation — such as the insertion of vertical blank spaces across the staff systems delimiting informational units — can lead to increased fluency and accuracy in sightreading. We are currently extending this work to broader ranges of expertise and musical repertoires; we are also teaching musicians how to use digital music processing systems to reconfigure their own scores in these optimised ways. For more information see link.

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Latest news

Lottie Anstee receives PhD scholarship from Goldsmiths

21 February 2024

We are very pleased to hear that Lottie Anstee, former undergraduate student at the Centre for Music and Science, has just received a PhD scholarship from Goldsmiths, University of London. Lottie will be starting the PhD in September, working with Lauren Stewart and Katie Rose Sanfilippo. The project concerns developing a...

Xiaoxuan Wang secures PhD position at the Digital and Cognitive Musicology Lab at EPFL, Switzerland

2 February 2024

We are delighted for Xiaoxuan Wang, MPhil student at our Centre for Music and Science in 2022-23, who has just accepted a PhD position at the Digital and Cognitive Musicology Lab (DCML) at EPFL, Switzerland. The DCML is run by Martin Rohrmeier, himself an alumnus of the Centre for Music and Science. The current plan is to...