Archiv der Kategorie: Publications

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 →

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 →

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 →

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

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, … Weiterlesen →

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 … Weiterlesen →