Archiv der Kategorie: Publications

Paper describing Artificial Audio Multitracks (AAM) dataset published in EURASIP Journal on Audio, Speech, and Music Processing

Publiziert am 17. April 2023 von Igor Vatolkin

F. Ostermann, I. Vatolkin, and M. Ebeling: AAM: a Dataset of Artificial Audio Multitracks for Diverse Music Information Retrieval Tasks. EURASIP Journal on Audio, Speech, and Music Processing, 13, 2023. Zenodo link: https://doi.org/10.5281/zenodo.5794629 Abstract: We present a new dataset of … Weiterlesen →

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Two papers accepted for EvoMUSART

Publiziert am 26. Januar 2023 von Igor Vatolkin

(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 →

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Paper on multi-modal music classification accepted for ISMIR

Publiziert am 15. Juli 2022 von Igor Vatolkin

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

Publiziert am 3. Februar 2022 von Igor Vatolkin

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

Publiziert am 3. Dezember 2021 von Igor Vatolkin

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

Publiziert am 24. November 2021 von Igor Vatolkin

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

Publiziert am 25. April 2021 von Igor Vatolkin

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

Publiziert am 26. Juli 2020 von Igor Vatolkin

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

Publiziert am 1. November 2019 von Igor Vatolkin

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

Publiziert am 12. Januar 2019 von Igor Vatolkin

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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