Call for participation: Workshop and tutorial in Chemnitz

The German-speaking workshop “Musik trifft Informatik” (“music meets computer science”) will be supported with a tutorial on automatic music processing. Please see details below (in German):

GI Workshop: Musik trifft Informatik
47. Jahrestagung der Gesellschaft für Informatik e.V. (GI)
Chemnitz, Germany, 26 September 2017
https://www.audiolabs-erlangen.de/resources/MIR/2017-GI-Workshop-Musik/

GI Tutorial: Automatisierte Methoden der Musikverarbeitung
47. Jahrestagung der Gesellschaft für Informatik e.V. (GI)
Chemnitz, Germany, 25 September 2017
https://www.audiolabs-erlangen.de/resources/MIR/2017-GI-Tutorial-Musik/

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Two papers accepted for UMAP and AES

The following papers were accepted:

Kamehkhosh, I. and Jannach, D.: User Perception of Next-Track Music Recommendations. UMAP 2017, Bratislava, 2017

[describes a user case study on the evaluation of different algorithms for playlist generation with regard to perceived quality]

Scholz, F., Vatolkin, I., and Rudolph, G.: Singing Voice Detection across Different Music Genres. AES 2017), Erlangen, 2017

[compares three methods for recognition of vocals using distinct training and validation sets from six music genres]

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Call for papers: German-speaking workshop “Musik trifft Informatik” (“music meets computer science”), Chemnitz, 26.09.2017

Im Rahmen der 47. Jahrestagung der Gesellschaft für Informatik e.V. (GI) in Chemnitz findet ein Workshop zum Thema “Musik trifft Informatik” statt. Details zu Beiträgen und Inhalten findet man auf den folgenden Webseiten:

https://www.audiolabs-erlangen.de/resources/MIR/2017-GI-Workshop-Musik/
https://informatik2017.de/ws01-musik-trifft-informatik/

Wichtige Termine

  • Einreichung von Beiträgen: bis 23.04.2017
  • Entscheidung über die Annahme: bis 22.05.2017
  • Einreichung der druckfähigen Version: bis 30.06.2017
  • Workshop: 26.09.2017

Weiterhin wird es ein Tutorial zum Thema “Musikverarbeitung” geben. Details findet man auf den folgenden Webseiten:

https://www.audiolabs-erlangen.de/resources/MIR/2017-GI-Tutorial-Musik/
https://informatik2017.de/tut01-musikverarbeitung/
Termin: 25.09.2017

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Project group “The Reactive Jukebox” starts in summer term

The student project group “The Reactive Jukebox” (supervised by D. Jannach and I. Vatolkin) will start in summer term 2017.

The goal of the project is to develop an application for music recommendation with an interactive interface to listener requests. Such interaction should be done in an intuitive and user-friendly way, for instance providing feeback in a spoken language or describing music with the help of interpretable semantic features (“please recommend me faster songs with more distorted guitars and more vocal segments”). For the indexing of music, it is planned to integrate features of different sources, like community tags, meta data, audio descriptors, or symbolic characteristics.

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Two papers accepted for EvoMUSART

F. Ostermann, I. Vatolkin, G. Rudolph: Evaluation Rules for Evolutionary Generation of Drum Patterns in Jazz Solos. Proceedings of the 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017), Amsterdam, 2017

I. Vatolkin: Generalisation Performance of Western Instrument Recognition Models in Polyphonic Mixtures with Ethnic Samples. Proceedings of the 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017), Amsterdam, 2017

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Bachelor thesis on vocal recognition

The thesis “Florian Scholz: Gesangserkennung in polyphonen Musikaufnahmen” (Vocal recognition in polyphonic music recordings, PDF in German) compares several methods for supervised recognition of vocals in music tracks. In particular, experiments with training and test sets of different genres are investigated.

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Update: exercises for music data analysis textbook

On the music data analysis textbook web page, the exercises manual is now available for download.

Update 23.12.2016: The newer version of exercises and the list of errata were uploaded to the book web page.

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SIGMA #37

The program of the following 37th SIGMA meeting on 19.12.2016, 14:00-16:20, which takes place at Faculty of Statistics, TU Dortmund, Mathematics Building, room M/E27
(talks on bachelor theses in German):

14:00-14:05 Welcome greetings

14:05-14:30 Bachelor thesis
Alex Runge: Analysis of energy features for prediction of emotions in music

14:30-14:55 Bachelor thesis
Philipp Hallmeier: Modelling of frequency and amplitude modulation

14:55-15:20 Bachelor thesis + Demo
Fabian Ostermann: Generation of drum accompaniment to improvised Jazz solos

15:20-15:30 Short break

15:30-15:45 Bachelor thesis
Florian Scholz: Recognition of vocals in polyphonic music recordings

15:45-16:00 ISMIR conference paper
Daniel Stoller: Analysis and classification of phonation modes in singing

16:00-16:20 Coursebook on music data analysis, teaching exercises and slides, miscellaneous, next meeting

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Online survey on music recommendation

The e-Services research group of the computer science department, TU Dortmund is conducting a user study about automated music recommendation and would like to invite you to participate in an online experiment. The experiment takes about 10 minutes. You will be asked to listen to a few song excerpts and to give feedback on them. Start the experiment here: http://bit.ly/ls13-mus. Thank you!

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Music data analysis book is published

The textbook on music data analysis is now published.

Weihs, C., Jannach, D., Vatolkin, I., Rudolph, G. (Eds.):
Music data analysis: foundations and applications

For the list of chapters, see http://sig-ma.de/music-data-analysis-book

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