2024
Weighted Initialisation of Evolutionary Instrument and Pitch Detection in Polyphonic Music
J. Dettmer, I. Vatolkin, and T. Glasmachers
Proceedings of the 13th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
Adaptation and Optimization of AugmentedNet for Roman Numeral Analysis Applied to Audio Signals
L. Fricke, M. Gotham, F. Ostermann, and I. Vatolkin
Proceedings of the 13th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
2023
AAM: A Dataset of Artificial Audio Multitracks for Diverse Music Information Retrieval Tasks
F. Ostermann, I. Vatolkin, M. Ebeling
EURASIP Journal on Audio, Speech, and Music Processing, Volume 2023
Application of Neural Architecture Search to Instrument Recognition in Polyphonic Audio
L. Fricke, I. Vatolkin, and F. Ostermann
Proceedings of the 12th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
Musical Genre Recognition based on Deep Descriptors of Harmony, Instrumentation, and Segments
I. Vatolkin, M. Gotham, N. Nápoles López, and F. Ostermann
Proceedings of the 12th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
2022
Multi-Objective Investigation of Six Feature Source Types for Multi-Modal Music Classification
I. Vatolkin and C. McKay
Transactions of the International Society for Music Information Retrieval, 5(1):1-19
Suppression of Background Noise in Speech Signals with Artificial Neural Networks, Exemplarily Applied to Keyboard Sounds
L. Fricke, J. Kuzmic, and I. Vatolkin
Proceedings of the 14th International Conference on Neural Computation Theory and Applications (NCTA), pp. 367-374
Stability of Symbolic Feature Group Importance in the Context of Multi-Modal Music Classification
I. Vatolkin and C. McKay
Proceedings of the The 23rd International Society for Music Information Retrieval Conference (ISMIR), pp.469-476
Artificial Music Producer: Filtering Music Compositions by Artificial Taste
F. Ostermann, I. Vatolkin, and G. Rudolph
Proceedings of the 3rd Conference on AI Music Creativity (AIMC)
Identification of the Most Relevant Zygonic Statistics and Semantic Audio Features for Genre Recognition
I. Vatolkin
Proceedings of the International Computer Music Conference (ICMC)
2021
Evaluating Creativity in Automatic Reactive Accompaniment of Jazz Improvisation
F. Ostermann, I. Vatolkin, and G. Rudolph
Transactions of the International Society for Music Information Retrieval, 4(1):210-222
Statistical and Visual Analysis of Audio, Text, and Image Features for Multi-Modal Music Genre Recognition.
B. Wilkes, I. Vatolkin, and H. Müller
Entropy, 23(11)
Improving Interpretable Genre Recognition with Audio Feature Statistics Based on Zygonic Theory
I. Vatolkin
Proceedings of the 2nd Nordic Sound and Computing Conference (NordicSMC)
Advancements in the Music Information Retrieval Framework AMUSE over the Last Decade
I. Vatolkin, P. Ginsel, and G. Rudolph
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp. 2383-2389
An Evolutionary Multi-Objective Feature Selection Approach for Detecting Music Segment Boundaries of Specific Types
I. Vatolkin, F. Ostermann, and M. Müller
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 1061-1069
A Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features
I. Vatolkin, B. Adrian, and J. Kuzmic
Proceedings of the 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 313-326
A Multi-Objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation
I. Vatolkin, M. Koch, and M. Müller
Proceedings of the 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 327-343
2020
Evolutionary Approximation of Instrumental Texture in Polyphonic Audio Recordings
I. Vatolkin
Proceedings of the IEEE World Congress on Computational Intelligence (WCCI), Glasgow, UK
Analysis of Structural Complexity Features for Music Genre Recognition
P. Ginsel, I. Vatolkin, and G. Rudolph
Proceedings of the IEEE World Congress on Computational Intelligence (WCCI), Glasgow, UK
Harmonic/Percussive Sound Separation and Spectral Complexity Reduction of Music Signals for Cochlear Implant Listeners
B. Lentz, A. Nagathil, J. Gauer, and R. Martin
Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8713-8717, Barcelona, Spain
Comparing Fuzzy Rule Based Approaches for Music Genre Classification
F. Heerde, I. Vatolkin, and G. Rudolph
Proceedings of the 9th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 35-48, Seville, Spain
2019
Applications in Statistical Computing: From Music Data Analysis to Industrial Quality Improvement
N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, M. Vichi (Eds.)
Springer
Evolutionary Multi-Objective Training Set Selection of Data Instances and Augmentations for Vocal Detection
I. Vatolkin, D.Stoller
Proceedings of the 8th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 201-216, Leipzig, Germany
2018
Intuitive and Efficient Computer-Aided Music Rearrangement with Optimised Processing of Audio Transitions
D. Stoller, I. Vatolkin, H. Müller
Journal of New Music Research, 47(5):416-437
Robustness of Features and Classification Models on Degraded Data Sets in Music Classification
I. Vatolkin
Accepted for Archives of Data Science, Series A
Classifying Music Genres Using Image Classification Neural Networks
A. K. Hassen, H. Janßen, D. Assenmacher, M. Preuss, and I. Vatolkin
Archives of Data Science, Series A, 5(1):1-18, 2018
Comparison of Audio Features for Recognition of Western and Ethnic Instruments in Polyphonic Mixtures
I. Vatolkin, G. Rudolph
Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), pp. 554-560
2017
User Perception of Next-Track Music Recommendations
I. Kamehkhosh, D. Jannach
Accepted for Proceedings of the 25th Conference on User Modelling, Adaptation and Personalization (UMAP), Bratislava, Slovakia
Singing Voice Detection across Different Music Genres
F. Scholz, I. Vatolkin, G. Rudolph
Accepted for Proceedings of the 2017 AES Conference on Semantic Audio, Erlangen, Germany
Evaluation Rules for Evolutionary Generation of Drum Patterns in Jazz Solos
F. Ostermann, I. Vatolkin, G. Rudolph
Accepted for Proceedings of the 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), Amsterdam, The Netherlands
Generalisation Performance of Western Instrument Recognition Models in Polyphonic Mixtures with Ethnic Samples
I. Vatolkin
Accepted for Proceedings of the 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), Amsterdam, The Netherlands
2016
Biases in Automated Music Playlist Generation: A Comparison of Next-Track Recommending Techniques, User Modeling, Adaptation and Personalization
D. Jannach, I. Kamehkhosch, G. Bonnin
Proceedings of User Modeling, Adaptation and Personalization (UMAP), pp. 281-285, Halifax, Canada
Spectral Complexity Reduction of Music Signals for Mitigating Effects of Cochlear Hearing Loss
A. Nagathil, C. Weihs, R. Martin
IEEE/ACM Transactions on Audio, Speech, and Language Processing, 24(3):445-458
2015
Evaluation of Album Effect for Feature Selection in Music Genre Recognition
I. Vatolkin, G. Rudolph, C. Weihs
Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR), pp. 169-175, Malaga, Spain
Beyond “Hitting the Hits” – Generating Coherent Music Playlist Continuations with the Right Tracks
D. Jannach, L. Lerche, I. Kamehkhosh
Proceedings of the 9th ACM Conference on Recommender Systems (RecSys), pp. 187-194, Vienna, Austria
Interpretability of Music Classification as a Criterion for Evolutionary Multi-Objective Feature Selection
I. Vatolkin, G. Rudolph, C. Weihs
Proceedings of the 4th European Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART), pp. 236-248, Copenhagen, Denmark
Exploration of Two-Objective Scenarios on Supervised Evolutionary Feature Selection: a Survey and a Case Study (Application to Music Categorisation)
I. Vatolkin
Proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization (EMO), pp. 529-543, Guimarães, Portugal
Comparing Audio Features and Playlist Statistics for Music Classification
I. Vatolkin, G. Bonnin, D. Jannach
Proceedings of the 2nd European Conference on Data Analysis (ECDA 2014), Bremen, Germany
2014
Automated Generation of Music Playlists: Survey and Experiments
G. Bonnin and D. Jannach
ACM Computing Surveys, Vol. 47, No. 2, Article 26
Analyzing the Characteristics of Shared Playlists for Music Recommendation
D. Jannach, I. Kamehkhosh, G. Bonnin
Proceedings of the 6th ACM RecSys Workshop on Recommender Systems and Social Web
Interpretable Music Categorisation based on Fuzzy Rules and High-Level Audio Features Features
I. Vatolkin and G. Rudolph
Accepted for Proceedings of the 2013 European Conference on Data Analysis (ECDA), Luxembourg, Luxembourg
Impact of Frame Size and Instrumentation on Chroma-based Automatic Chord Recognition
D. Stoller, M. Mauch, I. Vatolkin and C. Weihs
Accepted for Proceedings of the 2013 European Conference on Data Analysis (ECDA), Luxembourg, Luxembourg
2013
Evaluating the Quality of Generated Playlists Based on Hand-Crafted Samples
G. Bonnin and D. Jannach
Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR), pp. 263-268, Curitiba, Brazil
Measuring the Performance of Evolutionary Multi-Objective Feature Selection for Prediction of Musical Genres and Styles
I. Vatolkin
Proceedings of the 2nd Workshop Audiosignal- und Sprachverarbeitung (WASP) at INFORMATIK 2013, pp. 3012-3025, Koblenz, Germany
A Comparison of Playlist Generation Strategies for Music Recommendation and a New Baseline Scheme
G. Bonnin and D. Jannach
Accepted for AAAI 2013 Workshop on Intelligent Techniques For Web Personalization and Recommender Systems (ITWP 2013), pp. 16-23, Bellevue, USA
Audio Signal Classification in Reverberant Environments Based on Fuzzy-Clustered Ad-hoc Microphone Arrays
S. Gergen, A. Nagathil and R. Martin
Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 3692-3696, Vancouver, Canada
Performance of Specific vs. Generic Feature Sets in Polyphonic Music Instrument Recognition
I. Vatolkin, A. Nagathil, W. Theimer and R. Martin
Proceedings of the 7th International Conference on Evolutionary Multi-Criterion Optimization (EMO), pp. 587-599, Sheffield, UK
2012
Multi-Objective Evolutionary Feature Selection for Instrument Recognition in Polyphonic Audio Mixtures
I. Vatolkin, M. Preuß, G. Rudolph, M. Eichhoff and C. Weihs
Soft Computing – A Fusion of Foundations, Methodologies and Applications, 16(12):2027-2047
Music and Timbre Segmentation by Recursive Constrained K-means Clustering
S. Krey, U. Ligges and F. Leisch
Computational Statistics, published online
Tone Onset Detection Using an Auditory Model
N. Bauer, K. Friedrichs, J. Schiffner and C. Weihs
Accepted for Proceedings of the 36th Annual Conference of the German Classification Society (GfKl), Hildesheim, Germany
Detection of Musical Instruments in Intervals and Chords
M. Eichhoff and C. Weihs
Accepted for Proceedings of the 36th Annual Conference of the German Classification Society (GfKl), Hildesheim, Germany
Statistical Comparison of Classifiers for Multi-Objective Feature Selection in Instrument Recognition
I. Vatolkin, B. Bischl, G. Rudolph and C. Weihs
Accepted for Proceedings of the 36th Annual Conference of the German Classification Society (GfKl), Hildesheim, Germany
Music Genre Prediction by Low-Level and High-Level Characteristics
I. Vatolkin, G. Rötter and C. Weihs
Accepted for Proceedings of the 36th Annual Conference of the German Classification Society (GfKl), Hildesheim, Germany
Training Set Reduction Based on 2-Gram Feature Statistics for Music Genre Recognition
I. Vatolkin, M. Preuss and G. Rudolph
Proceedings of the 2012 Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML), Dortmund, Germany
BeatTheBeat: Music-Based Procedural Content Generation In a Mobile Game
A. Jordan, D. Scheftelowitsch, J. Lahni, J. Hartwecker, M. Kuchem, M. Walter-Huber, N. Vortmeier, T. Delbruegger, Ü. Güler, I. Vatolkin and M. Preuss
Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games (CIG), pp. 320-327, Granada, Spain
2011
Towards an Automated Dynamic Organization of Huge Music Archives on Mobile Devices
H. Blume, B. Bischl, M. Botteck, C. Igel, R. Martin, G. Rötter, G. Rudolph, W. Theimer, I. Vatolkin and C. Weihs
IEEE Signal Processing Magazine, 28(4), July 2011
Comparison of Classical and Sequential Design of Experiments in Note Onset Detection
N. Bauer, J. Schiffner and C. Weihs
Accepted for Proceedings of the 35th Annual Conference of the German Classification Society (GfKl), Frankfurt, Germany
A Case Study about the Effort to Classify Music Intervals by Chroma and Spectrum Analysis
V. Mattern, I. Vatolkin and G. Rudolph
Accepted for Proceedings of the 35th Annual Conference of the German Classification Society (GfKl), Frankfurt, Germany
Computational Prediction of High-Level Descriptors of Music Personal Categories
G. Rötter, I. Vatolkin and C. Weihs
Accepted for Proceedings of the 35th Annual Conference of the German Classification Society (GfKl), Frankfurt, Germany
High Performance Hardware Architectures for Automated Music Classification
I. Schmädecke and H. Blume
Accepted for Proceedings of the 35th Annual Conference of the German Classification Society (GfKl), Frankfurt, Germany
Regression-Based Tempo Recognition from Chroma and Energy Accents for Slow Audio Recordings
T. Deinert, I. Vatolkin and G. Rudolph
Proceedings of the AES 42nd International Conference on Semantic Audio (AES), pp. 60-68, Ilmenau, Germany
Multi-Objective Feature Selection in Music Genre and Style Recognition Tasks
I. Vatolkin, M. Preuß and G. Rudolph
Proceedings of the 2011 Genetic and Evolutionary Computation Conference (GECCO), Dublin, Ireland
GPU-based Acoustic Feature Extraction for Electronic Media Processing
I. Schmädecke, J. Mörschbach and H. Blume
Proceedings of the 14th ITG Conference on Electronic Media Technology, Dortmund, Germany
Feature Clustering for Instrument Classification
U. Ligges and S. Krey
Computational Statistics 26 (2), 279-291
2010
AMUSE (Advanced MUSic Explorer) – A Multitool Framework for Music Data Analysis
I. Vatolkin, W. Theimer and M.Botteck
Proceedings of the 11th International Society for Music Information Retrieval Conference (ISMIR), pp. 33-38, Utrecht, Netherlands
Software in Music Information Retrieval (MIR)
C. Weihs, K. Friedrichs, M. Eichhoff and I. Vatolkin
Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), pp. 421-432, Karlsruhe, Germany
Partition Based Feature Processing for Improved Music Classification
I. Vatolkin, W. Theimer and M. Botteck
Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), pp. 411-419, Karlsruhe, Germany
Multi-Objective Evaluation of Music Classification
I. Vatolkin
Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), pp. 401-410, Karlsruhe, Germany
Musical Instrument Recognition by High-Level Features
M. Eichhoff and C. Weihs
Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), pp. 373-381, Karlsruhe, Germany
SVM based Instrument and Timbre Classification
S. Krey and U. Ligges
Classification as a Tool for Research. Proceedings of the 11th IFCS Biennial Conference and 33rd Annual Conference of the Gesellschaft für Klassifikation e.V., pp. 759-766, Dresden, Germany, Springer-Verlag, Berlin
2009
Design and Comparison of Different Evolution Strategies for Feature Selection and Consolidation in Music Classification
I. Vatolkin, W. Theimer and G. Rudolph
Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC), pp. 174-181, Trondheim, Norway
2008
Definitions of Audio Features for Music Content Description
W. Theimer, I. Vatolkin and A. Eronen
Technical Report TR08-2-001, Chair of Algorithm Engineering, University of Dortmund
2007
Classification in Music Research
C. Weihs, U. Ligges, F. Mörchen and D. Müllensiefen
Advances in Data Analysis and Classification 1 (3), 255-29span style=“color: #0000ff;“