Author: Daniel
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Digital Musicology Workshop @ Digital Humanities at Oxford Summer School (DHOxSS)
The Digital Humanities at Oxford Summer School (DHOxSS) is an annual Digital Humanities training event. DHOxSS delegates are introduced to a range of topics suitable for researchers, project managers, research assistants, and students who are interested in the creation, management, analysis, modelling, visualization, or publication of digital data for the humanities. Tillman Weyde, PI of…
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MIRG @ British Library Digital Conversations: 21st May 2015, 6PM
City University is prominently featured in the upcoming British Library event “Digital Conversations” – with Tillman Weyde representing the Music Informatics Group and the Stephen Cottrell from the Music Department. Tillman will present the Digital Music Lab project which enables music research on big datasets. Further speakers include Sandra Tuppen (A Big Data History of…
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Digital Music Lab Workshop on Analysing Big Music Data at City University on March 19th
This March, City University is looking forward to host the first workshop of the DML project, a collaboration of City University London, Queen Mary University of London, University College London, and the British Library towards enabling music research on large datasets: Digital Music Lab 1st Workshop on Analysing Big Music Data 19 March 2014, 10:00…
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Learning Similarity with RBM Features + Updated CAMIR Code
This page allows you to reproduce the experiments from our paper “Feature Preprocessing using RBM for Music Similarity Learning“. This includes the newest release of the CAMIR system for modelling music similarity. MLR and SVMLIGHT were tested using a framework developed by Daniel Wolff (daniel.wolff.1@city.ac.uk) at the MIRG group. This version of CAMIR contains the…
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Creating Audio Based Experiments as Social Web Games with the CASimIR Framework
Download the newest release of the CASIMIR system for creating experiments as social web games and surveys You can download the code using gitfrom the following repository. It is licensed under the GNU GPL v3. https://github.com/citymirg/casimir The data collected via Spot The Odd Song Out can be downloaded below: stosoaes2013_r1298.zip The data is licensed under…
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Spot the Odd Song Out collects Music Similarity Data
[Update August 2018] Unfortunately Spot the Odd Song Out is offline as it needs some updates to the latest web developments. If you are interested contributing to the development of a modern music-based Games-With-A-Purpose platform, please contact Daniel directly at [daniel(dot)wolff(dot)2(at)city.ac.uk]. A video of the game can be seen below. Spot the Odd Song Out…
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The MagnaTagATune Dataset
As the domain tagatune.org has gone offline, with kind permission of the original authors, we now host the MagnaTagATune dataset at City University. The data was collected using the TagATune game and music from the Magnatune label. Credit for collecting this handy dataset goes to Edith Law, Olivier Gillet, and the authors below. If you…
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Reading Group Meeting 12.06.2013: Group-theoretic approaches to indexing and retrieval of music and multimedia
We are meeting up on Wednesday June 12th, at 4:30pm in AG06 for our next MIRG reading group! This session, we will discuss Group-theoretic approaches to indexing and retrieval of music and multimedia databases as in the paper by Michael Clausen , Heiko Körner , Frank Kurth (2003): An Efficient Indexing and Search Technique for…
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The CAMIR System
Download the newest release of the CAMIR system for modelling music similarity MLR and SVMLIGHT were tested using a framework developed by Daniel Wolff at the MIRG group. You can download the code using subversion from the following repository: user: anonymous pass: citymirg http://chivm.soi.city.ac.uk/svn/camir/branches/code_publications/ISMIR2012
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Music Similarity Adaptation: Wolff + Stober @ ISMIR 2012
The Paper: A Systematic Comparison of Music Similarity Adaptation Approaches Daniel Wolff1, Sebastian Stober2, Andreas Nürnberger2, Tillman Weyde1 1City University London, 2Otto-von-Guericke-Universität Magdeburg Thanks for all the attention we got for our collaborative publication, we’re now finally releasing the code to ensure reproducibility of the experiments. Feel free to reuse and adapt the code but please cite the…