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SUMMARY:An IDyOM Tutorial: Modelling Auditory Expectations - Dr Marcus Pea
 rce - Queen Mary\, University of London.
DTSTART:20150127T170000Z
DTEND:20150127T190000Z
UID:TALK57561@talks.cam.ac.uk
CONTACT:David Greatrex
DESCRIPTION:IDyOM  - Information Dynamics of Music (Pearce\, 2005) – is 
 a computational model of auditory expectation. It acquires knowledge of mu
 sical structure through statistical learning of sequential dependencies be
 tween notes in the music to which it is exposed. The model generates a con
 ditional probability distribution governing the next note in a sequence\, 
 given the preceding notes. The entropy of this distribution reflects the m
 odel's uncertainty about the next note\, while the negative log probabilit
 y (information content) of the note that actually follows reflects how une
 xpected that note is to the model. With training on an appropriate corpus 
 of music\, research using EEG\, behavioural and physiological methods has 
 shown that information content and entropy accurately predict listeners’
  ongoing expectations while listening to music (Egermann et al.\, 2013\; H
 ansen & Pearce\, 2014\; Omigie et al.\, 2012\, 2013\; Pearce\, 2005\; Pear
 ce et al.\, 2010). The tutorial will cover: a) importing databases of musi
 c\; b) extracting symbolic music features (relating to pitch\, timing etc.
  of musical events) from the database\; c) running the model to generate p
 robabilistic descriptions of musical structure including examples using di
 fferent training data\, model configurations and musical features.\n\nMarc
 us Pearce is a lecturer in Sound and Music Processing at Queen Mary\, Univ
 ersity of London. In addition he leads the Music Cognition Lab\, is the di
 rector of the EEG Laboratory and co-director of the Centre for Mind in Soc
 iety: http://webprojects.eecs.qmul.ac.uk/marcusp/
LOCATION:Lecture Room 1\, Faculty of Music\, 11 West Road\, CB3 9DP
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