Archiv der Kategorie: MIR Research
Two papers accepted for EvoMUSART
(1) I. Vatolkin, M. Gotham, N. Nápoles López, and F. Ostermann: Musical Genre Recognition based on Deep Descriptors of Harmony, Instrumentation, and Segments. Accepted for Proceedings of the 12th International Conference on Artificial Intelligence in Music, Sound, Art and Design … Weiterlesen
Paper on multi-modal music classification accepted for ISMIR
I. Vatolkin and C. McKay: Stability of Symbolic Feature Group Importance in the Context of Multi-Modal Music Classification. accepted for Proceedings of the 23rd International Society for Music Information Retrieval Conference (ISMIR) Abstract: Multi-modal music classification creates supervised models trained … Weiterlesen
Paper on multi-modal music classification using six modalities published in TISMIR
I. Vatolkin and C. McKay: Multi-Objective Investigation of Six Feature Source Types for Multi-Modal Music Classification. Transactions of the International Society for Music Information Retrieval, 5(1), pp.1–19, 2022. Abstract: Every type of musical data (audio, symbolic, lyrics, etc.) has its … Weiterlesen
Paper on EAR Drummer accepted for TISMIR special collection on AI and Musical Creativity
F. Ostermann, I. Vatolkin, and G. Rudolph: Evaluating Creativity in Automatic Reactive Accompaniment of Jazz Improvisation Abstract: Music generating computer programs can support jazz musicians and students during performance and practice, for instance by providing accompaniment for solo improvisation. However, … Weiterlesen
Paper on multi-modal music classification accepted for Entropy
The following paper was accepted for Entropy: B. Wilkes, I. Vatolkin, and H. Müller: Statistical and Visual Analysis of Audio, Text, and Image Features for Multi-Modal Music Genre Recognition
Job offer for a student assistant
For assistance during software project „Music Informatics“, a position as a student assistant (8 hours per week) is offered at the Chair of Algorithm Engineering, Department of Computer Science, TU Dortmund. Please see the full description in German.
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 … Weiterlesen
AMUSE Repository Moved
The repository of Advanced MUSic Explorer has moved to: https://github.com/AdvancedMUSicExplorer/AMUSE
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 … Weiterlesen
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 … Weiterlesen