SIGMA #49

The program of the following 49th SIGMA meeting on 18.06.2021, 10:00-12:10, which takes place online
(please send an email to igor.vatolkin [at] udo.edu if you wish to get the Zoom link):

10:00-10:05 Welcome greetings

10:05-10:25 Conference study
Maria Heinze, Frieder Stolzenburg (Hochschule Harz): Harmony cognition by neural transformation – an analysis by EEG

10:25-10:55 Master’s thesis (results)
Fabian Ostermann: Modelling of listener music preferences with neural networks

10:55-11:15 Bachelor’s thesis (results)
Pauline Speckmann: Integration of clustering in AMUSE

11:15-11:35 Master’s thesis (introduction)
Philipp Ginsel: Distance measures for evolutionary approximation of audio data

11:35-12:00 Conference presentation + development plan
Igor Vatolkin, Philipp Ginsel: Changes in AMUSE since its presentation at ISMIR 2010 / development plan for the next years

12:00-12:10 Ongoing teachning courses, conferences and calls, miscellaneous, next meeting

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AMUSE paper accepted for SIGIR

The following paper was accepted for SIGIR conference:

I. Vatolkin, P. Ginsel, and G. Rudolph: Advancements in the Music Information Retrieval Framework AMUSE over the Last Decade

Before the presentation at SIGIR, we will update the user manual (the current version is available at https://github.com/AdvancedMUSicExplorer/AMUSE/blob/master/amuse/docs/user_manual.pdf)

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SIGMA #48

The program of the following 48th SIGMA meeting on 15.03.2021, 14:00-16:15, which takes place online
(please send an email to igor.vatolkin [at] udo.edu if you wish to get the Zoom link):

14:00-14:05 Welcome greetings

14:05-14:40 Master’s thesis (final results)
Stephan Steup: Perception and Production of Polyrhythms: an Empiric Study

14:40-15:20 Research proposal
Nezar Dasan: Development of Automatic Proofreading for Speech to Text Applications in Arabic Language

15:20-15:40 Bachelor’s thesis (introduction)
Pauline Speckmann: Integration of Clustering in AMUSE

15:40-16:00 Master’s thesis (introduction)
Florian Scholz: Inclusion of Different Instrument Bodies for Robust Training of Neural Networks for Instrument Recognition

16:00-16:15 Ongoing teachning courses, conferences and calls, miscellaneous, next meeting

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AMUSE Repository Moved

The repository of Advanced MUSic Explorer has moved to:

https://github.com/AdvancedMUSicExplorer/AMUSE

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Teaching in Winter Term 2020/2021

Two courses will take place during the winter term at TU Dortmund (web pages in German):

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Master Thesis on Instrument Recognition

The thesis „Benedikt Adrian: Implementierung von hybriden Methoden zur Instrumentenerkennung in verrauschten Musikdaten“ (Implementation of Hybrid Methods for Instrument Recognition in Noisy Music Data, PDF in German) applies CNNs together with shallow classifiers for the recognition of instruments in polyphonic audio signals and measures the impact of data augmentation for the training of classification models.

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Two Papers Presented at WCCI 2020

Two papers were presented during WCCI 2020:

Vatolkin, I.: Evolutionary Approximation of Instrumental Texture in Polyphonic Audio Recordings

[evaluates new features based on evolutionary approximation of instrumental texture for instrument and genre recognition]

Ginsel, P., Vatolkin, I. Rudolph, G.: Analysis of Structural Complexity Features for Music Genre Recognition

[provides an analysis of different parameters and features for structural complexity estimation applied to genre recognition]

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SIGMA #47

The program of the following 47th SIGMA meeting on 19.06.2020, 14:00-16:15, which takes place online:
https://tu-dortmund.zoom.us/j/94868569943?pwd=dXJFK3dvS3VMV1lWMTVYRFBhcENpdz09

14:00-14:05 Welcome greetings

14:05-14:25 Conference study
Benjamin Lentz: Harmonic/Percussive Sound Separation and Spectral Complexity Reduction of Music Signals for Cochlear Implant Listeners

14:25-15:00 Master thesis and extended study
Marcel Koch: Identification of Effective Features for Novelty Based Music Segmentation
Igor Vatolkin: Multi-Objective Feature Selection for Music Segmentation

15:00-15:35 Master thesis and extended study
Benedikt Adrian: Implementation of Hybrid Methods for Instrument Recognition in Noisy Music Data
Igor Vatolkin: Analysis of Instrument and Timbre Features for Genre Recognition

15:35-15:55 Database demo
Fabian Ostermann: Further Development of Database with Artificial Tracks for Multiple Classification Tasks

15:55-16:15 Teachning courses in winter term, miscellaneous, next meeting

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Call for Papers: GECCO DETA Track

Digital Entertainment Technologies and Arts Track @ GECCO in Cancun, Mexico, July 8th-12th 2020, invites for submissions describing original work involving the use of computational intelligence techniques in the creative arts, including design, games, and music. Works of a methodological, experimental, or theoretical nature within the context of digital entertainment and its application in industry will also be considered.

Full papers of at most 8 pages (excluding references) should present original work that meets the high-quality standards of GECCO. Accepted full papers appear in the ACM digital library as part of the Main Proceedings of GECCO. For full papers, a separate abstract needs to be submitted first by January 30, 2020. Full papers are due by the non-extensible deadline of February 6, 2020.

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New book: Applications in Statistical Computing

The book Bauer, N., Ickstadt, K., Lübke, K., Szepannek, G., Trautmann, H., Vichi, M (Eds.): Applications in Statistical Computing: From Music Data Analysis to Industrial Quality Improvement, Springer, has recently been published. This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.

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