Archiv der Kategorie: Publications

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

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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

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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

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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

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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 … Weiterlesen

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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 … Weiterlesen

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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 … Weiterlesen

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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

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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

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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, … Weiterlesen

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