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  • 16. Bannister - pseudo-social music listening experiences
    2024/01/23

    Scott Bannister is the first guest of the new year and in this episode, he can be heard discussing his work on musical chills, his work on the Cadenza project to improve the experience of music for listeners with hearing loss, and his latest work on the social experience of solo music listening.


    You can find out more on out website: https://mus-cog-matters.glitch.me/

    Find out more about the Cadenza Project here: https://cadenzachallenge.org/



    Hosted on Acast. See acast.com/privacy for more information.

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    46 分
  • 15. Collins - Computational modelling of music cognition
    2023/11/28

    MCM Founding member Tom Collins can be heard discussing his latest entry to the AI song content, computational modeling of music cognition, and the benefits these methods may offer music psychologists.


    You can find out more on out website: https://mus-cog-matters.glitch.me/

    Listen to VTGO by Kemi Sulola, Harriet Raynor, and Rebel Algorithms in full here: https://vtgo.glitch.me/


    Episode produced by Ben Forsdick


    Hosted on Acast. See acast.com/privacy for more information.

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    28 分
  • 14. Onderdijk - Virtual Musicking
    2023/10/24

    Kelsey Onderdijk can be heard discussing musicking in virtually mediated contexts with a focus on connectedness. She considers (temporal) co-presence and parasocial interaction, as well as the 'who' and 'why' of virtual (reality) concerts.


    Episode produced by Ben Forsdick


    Hosted on Acast. See acast.com/privacy for more information.

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    26 分
  • 13. Price - Understanding audiences
    2023/10/03

    In this episode, Dr. Sarah Price discusses her former, current, and future research on audiences of the arts.


    Episode produced by Ben Forsdick


    Hosted on Acast. See acast.com/privacy for more information.

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    30 分
  • 12. Temperley - Uniform Information Density
    2023/09/26

    In this episode, composer, music theorist, and cognitive scientist David Temperley, discusses the application of uniform information density to musical performance. David is a professor of music theory at the Eastman School of Music and uses 2000, he has been a professor of music theory at Eastman School of Music, you can listen to his original compositions on his website: http://davidtemperley.com/


    Episode produced by Ben Forsdick


    Hosted on Acast. See acast.com/privacy for more information.

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    32 分
  • 11. Norton - Researching students
    2023/09/19

    In the first episode of our second series Dr. Naomi Norton of the University of York discusses the ethical considerations when your students and participant sample overlap.


    Episode produced by Ben Forsdick


    Hosted on Acast. See acast.com/privacy for more information.

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    27 分
  • 10. Küssner - Visual Imagery
    2023/06/27

    Mats Küssner is a Lecturer in the Department of Musicology and Media Studies at Humboldt-Universität in Berlin and a Visiting Research Fellow in the Department of Psychology at Goldsmiths, University of London. His research focuses on multimodal perception and mental imagery of music, emotional responses to music, and performance science.


    GAPS2: https://sites.google.com/view/gaps2/home?authuser=0


    Hosted on Acast. See acast.com/privacy for more information.

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    18 分
  • 9. Popescu - Language and Music
    2023/06/13

    Tudor Popescu comes from an engineering background and has subsequently obtained a PhD in Experimental Psychology from the University of Oxford. His main research interest is understanding the psychological and cultural foundations of music. He is currently a Principle Investigator in the Department of General Psychology at the University of Padova.


    Join us for the next Music Cognition Matters presentation 13:00BST, 16/06/23 https://mus-cog-matters.glitch.me/

    (To join a meeting, click on the Calendar link at the top. Once you see the calendar, click on the appropriate event, then “More details»”.)


    Hosted on Acast. See acast.com/privacy for more information.

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    37 分