Archiv der Kategorie: MIR Research
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
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 … Weiterlesen
Bachelor thesis on music genre classification with Fuzzy KNN
The thesis „Philipp Ginsel: Strukturelle Komplexitätsmerkmale zur Musikgenre-Klassifikation mit Fuzzy-k-nearest-Neighbors“ (Structural complexity features for music genre classification with Fuzzy-k-nearest-Neighbors, PDF in German) examines different settings for extraction of structural complexity for prediction of music genres with Fuzzy KNN. The tested … Weiterlesen
Paper accepted for EvoMUSART 2019
The paper on evolutionary multi-objective training set selection is accepted for EvoMUSART 2019: I. Vatolkin and D. Stoller: Evolutionary Multi-Objective Training Set Selection of Data Instances and Augmentations for Vocal Detection. EvoMUSART 2019, Leipzig, 2019
Journal article on music rearrangement published
The article on music rearrangement is published: D. Stoller, I. Vatolkin, and H. Müller: Intuitive and Efficient Computer-Aided Music Rearrangement with Optimised Processing of Audio Transitions. Journal of New Music Research, Routledge, 47(5):416-437, 2018
Start of the DFG-funded project on interpretable music segmentation
Today, the DFG-funded project „Evolutionary optimisation for interpretable music segmentation and music categorisation based on discretised semantic metafeatures“ is started. The main goal of the project is to develop new methods for the extraction of interpretable structural information of audio … Weiterlesen