Archiv des Autors: Igor Vatolkin

Course on music data analysis at TU Dortmund

In September 2016, the interdisciplinary course on music data analysis based on the textbook „Music Data Analysis: Foundations and Applications“ took place at the Faculty of Statistics, TU Dortmund. The course contained lectures, exercises, and an a written examination. The … Weiterlesen

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Bachelor thesis on the impact of cepstral features for emotion recognition

In the thesis „Philipp Kramer: Relevanz cepstraler Merkmale für Vorhersagen im Arousal-Valence Modell auf Musiksignaldaten“ (Relevance of cepstral features for predictions in arousal-valence model for music signals, PDF in German), several groups of features were analysed for the regression-based prediction … Weiterlesen

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Diploma thesis on feature processing for classification of instruments and genres

The task of the thesis „Ettiboa Adouakou: Zur Bedeutung verlaufspezifischer Merkmale bei Klassifikationsproblemen auf Musiksignaldaten“ (On the meaning of time-based feature aggregation for classification of audio signal data), PDF in German) was to compare several groups of time-based feature aggregation … Weiterlesen

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Invited talk by Prof. Gerald Langner

Prof. Dr. Gerald Langner from TU Darmstadt will give a talk „Der neuronale Code von Tonhöhe, Klang und Harmonie“ (The neural code of pitch, sound, and harmony) at the Institute of Music and Music Science, TU Dortmund on 6.7.2016, 14-16 … Weiterlesen

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Music data analysis book can be pre-ordered now!

Weihs, C., Jannach, D., Vatolkin, I., Rudolph, G. (Eds.): Music data analysis: foundations and applications. https://www.crcpress.com/Music-Data-Analysis-Foundations-and-Applications/Weihs-Jannach-Vatolkin-Rudolph/p/book/9781498719568 This book edited and co-authored by SIGMA members and several partners provides a comprehensive overview of music data analysis, from introductory material to advanced … Weiterlesen

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Proseminars on music data analysis and computational intelligence in games

In winter term 2016/2017, two proseminars will take place at Chair of Algorithm Engineering, TU Dortmund: „Actual challenges in music data analysis“ The topics for student talks and works should represent various MIR research areas and will be selected from … Weiterlesen

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UMAP paper accepted

Jannach, D., Kamehkhosch, I., Bonnin, G.: Biases in Automated Music Playlist Generation: A Comparison of Next-Track Recommending Techniques, User Modeling, Adaptation and Personalization (UMAP 2016), Halifax, CA, 2016 In this work, the results of a multi-metric comparison of different academic … Weiterlesen

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Master thesis on lyrics finished

Florian Treinat: Verwendung von Lyrics zur Generierung von Musik-Playlisten (Application of lyrics for generation of music playlists) (supervisors: Dietmar Jannach, Iman Kamehkhosh, e-Services Research Group, TU Dortmund) The goal of this work was to improve the quality of music recommendations … Weiterlesen

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Master thesis on Twitter music data finished

Mike Gösker: #nowplaying: Analyse musikbezogener Twitterdaten (Analysis of music-related Twitter data) (supervisors: Dietmar Jannach, Lukas Lerche, e-Services Research Group, TU Dortmund) In his master’s thesis Mike Gösker implemented and evaluated a set of techniques to generate music track recommendations based … Weiterlesen

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Bachelor thesis on generation of drum accompaniment to improvised Jazz solos

The goal of the thesis (PDF in German) was to develop a system for the automatic generation of drum accompaniment to improvised Jazz solos. This is solved by means of an evolutionary algorithm. A list of rules is defined for … Weiterlesen

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