Archiv der Kategorie: MIR Research

Bachelor thesis on optical recognition of bagpipe notation

Publiziert am 19. Juli 2017 von Igor Vatolkin

The thesis „Andreas Jöbges: Optische Erkennung von Dudelsacknotation“ (Optical recognition of bagpipe notation, PDF in German) presents a system which produces digital score in „BWW“ format from scanned music pieces with the help of neural networks trained for the recognition … Weiterlesen →

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User study on playlist generation

Publiziert am 29. Juni 2017 von Igor Vatolkin

E-Services Research Group, TU Dortmund currently conducts a study about creating music playlists and would like to invite you to participate in an online experiment. The experiment takes about 10-15 minutes. You will be asked to create a short playlist … Weiterlesen →

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Two papers accepted for UMAP and AES

Publiziert am 5. April 2017 von Igor Vatolkin

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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Two papers accepted for EvoMUSART

Publiziert am 17. Januar 2017 von Igor Vatolkin

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 →

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Bachelor thesis on vocal recognition

Publiziert am 10. Dezember 2016 von Igor Vatolkin

The thesis „Florian Scholz: Gesangserkennung in polyphonen Musikaufnahmen“ (Vocal recognition in polyphonic music recordings, PDF in German) compares several methods for supervised recognition of vocals in music tracks. In particular, experiments with training and test sets of different genres are … Weiterlesen →

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Update: exercises for music data analysis textbook

Publiziert am 8. Dezember 2016 von Igor Vatolkin

On the music data analysis textbook web page, the exercises manual is now available for download. Update 23.12.2016: The newer version of exercises and the list of errata were uploaded to the book web page.

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Online survey on music recommendation

Publiziert am 13. November 2016 von Igor Vatolkin

The e-Services research group of the computer science department, TU Dortmund is conducting a user study about automated music recommendation and would like to invite you to participate in an online experiment. The experiment takes about 10 minutes. You will … Weiterlesen →

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Music data analysis book is published

Publiziert am 31. Oktober 2016 von Igor Vatolkin

The textbook on music data analysis is now published. Weihs, C., Jannach, D., Vatolkin, I., Rudolph, G. (Eds.): Music data analysis: foundations and applications For the list of chapters, see http://sig-ma.de/music-data-analysis-book

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Bachelor thesis on the impact of cepstral features for emotion recognition

Publiziert am 13. Juli 2016 von Igor Vatolkin

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

Publiziert am 7. Juli 2016 von Igor Vatolkin

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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