[AUDITORY] Music note prediction: Computational modeling task (Tom Collins )


Subject: [AUDITORY] Music note prediction: Computational modeling task
From:    Tom Collins  <tomthecollins@xxxxxxxx>
Date:    Wed, 17 Jul 2019 13:42:46 -0400
List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>

--000000000000e6c221058de40539 Content-Type: text/plain; charset="UTF-8" With apologies for cross-posting... Call for participation: Patterns for Prediction task @xxxxxxxx MIREX2019 https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction We are looking for researchers whose computational models and/or algorithms have the ability to predict the next musical events (continuation), based on given, foregoing events (prime). We are also interested in models that may not make explicit predictions, but can estimate the likelihood of several alternative continuations. One facet of human nature comprises the tendency to form predictions about what will happen in the future. Music provides an excellent setting for the study of prediction, and we hope that this task will attract interest from fields such as signal processing, psychology, neuroscience, music theory, music informatics, and machine learning. Why "patterns" in "Patterns for Prediction"? This task emerged from an existing Pattern Discovery task, which ran 2013-17. The last five years have seen an increasing interest in discovering or generating patterned data, leveraging methods beyond typical (e.g., Markovian) limits. E.g., how might exact and inexact repetition, occurring over the short, medium, and long term in pieces of music, interact with expectations in order to form a basis for successful prediction? MIREX stands for the Music Information Retrieval Evaluation eXchange. Since 2005, it has provided a forum for researchers to (1) train algorithms to perform specific, music-technological tasks on publicly available datasets, (2) submit algorithms that are run and evaluated by MIREX organizers on private datasets, (3) compare their work with one another and shed light on research questions informed by and informing diverse fields intersecting with music informatics. The deadline for submitting to this task is Monday September 9th, 2019. If you are interested in participating in this task but do not think you will have time until the 2020 iteration, please let us know so we can keep you in mind for next year. For more details, please refer to the MIREX page: https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction Your task captains are Iris Yuping Ren (yuping.ren.iris), Berit Janssen (berit.janssen), James Owers (james.f.owers), and Tom Collins (tomthecollins, all at gmail.com). Feel free to copy in all four of us if you have questions/comments. Thanks for reading! Tom Collins, PhD http://tomcollinsresearch.net https://musicintelligence.co Lecturer (Assistant Professor) in Music Technology Department of Music University of York --000000000000e6c221058de40539 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">With apologies for cross-posting...<br><br>Call for partic= ipation: Patterns for Prediction task @xxxxxxxx MIREX2019<br><a href=3D"https://www= .music-ir.org/mirex/wiki/2019:Patterns_for_Prediction">https://www.music-ir= .org/mirex/wiki/2019:Patterns_for_Prediction</a><br><br>We are looking for = researchers whose computational models and/or algorithms have the ability t= o predict the next musical events (continuation), based on given, foregoing= events (prime). We are also interested in models that may not make explici= t predictions, but can estimate the likelihood of several alternative conti= nuations.<br><br>One facet of human nature comprises the tendency to form p= redictions about what will happen in the future. Music provides an excellen= t setting for the study of prediction, and we hope that this task will attr= act interest from fields such as signal processing, psychology, neuroscienc= e, music theory, music informatics, and machine learning.<br><br>Why &quot;= patterns&quot; in &quot;Patterns for Prediction&quot;? This task emerged fr= om an existing Pattern Discovery task, which ran 2013-17. The last five yea= rs have seen an increasing interest in discovering or generating patterned = data, leveraging methods beyond typical (e.g., Markovian) limits. E.g., how= might exact and inexact repetition, occurring over the short, medium, and = long term in pieces of music, interact with expectations in order to form a= basis for successful prediction?<br><br>MIREX stands for the Music Informa= tion Retrieval Evaluation eXchange. Since 2005, it has provided a forum for= researchers to (1) train algorithms to perform specific, music-technologic= al tasks on publicly available datasets, (2) submit algorithms that are run= and evaluated by MIREX organizers on private datasets, (3) compare their w= ork with one another and shed light on research questions informed by and i= nforming diverse fields intersecting with music informatics.<br><br>The dea= dline for submitting to this task is Monday September 9th, 2019. If you are= interested in participating in this task but do not think you will have ti= me until the 2020 iteration, please let us know so we can keep you in mind = for next year.<br><br>For more details, please refer to the MIREX page: <a = href=3D"https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction">h= ttps://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction</a><br><br>= Your task captains are Iris Yuping Ren (yuping.ren.iris), Berit Janssen (be= rit.janssen), James Owers (james.f.owers), and Tom Collins (tomthecollins, = all at <a href=3D"http://gmail.com">gmail.com</a>). Feel free to copy in al= l four of us if you have questions/comments.<br><br>Thanks for reading!<br>= <div><br></div><div><br></div><div>Tom Collins, PhD<br><a href=3D"http://to= mcollinsresearch.net">http://tomcollinsresearch.net</a><br><a href=3D"https= ://musicintelligence.co">https://musicintelligence.co</a><br>Lecturer (Assi= stant Professor) in Music Technology<br>Department of Music<br>University o= f York<br></div><div><br></div><div><br></div></div> --000000000000e6c221058de40539--


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