Publications

2023

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Michael Vötter, Maximilian Mayerl, Eva Zangerle and Günther Specht: Song Popularity Prediction using Ordinal Classification. In Proceedings of the 20th Sound and Music Computing Conference. June 15-17, 2023. Stockholm, Sweden. Royal College of Music and KTH Royal Institute of Technology, 2023

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Maximilian Mayerl, Michael Vötter, Günther Specht and Eva Zangerle: Pairwise Learning to Rank for Hit Song Prediction. In BTW 2023. Gesellschaft für Informatik e.V., 2023

2022

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Michael Vötter, Maximilian Mayerl, Günther Specht and Eva Zangerle: HSP Datasets: Insights on Song Popularity Prediction. In International Journal of Semantic Computing, pages 1-23. 2022 Publisher: World Scientific Publishing Co.

2021

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Maximilian Mayerl, Michael Vötter, Andreas Peintner, Günther Specht and Eva Zangerle: Recognizing Song Mood and Theme: Clustering-based Ensembles. In Working Notes Proceedings of the MediaEval 2021 Workshop. ceur-ws.org, 2021

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Michael Vötter, Maximilian Mayerl, Günther Specht and Eva Zangerle: Novel Datasets for Evaluating Song Popularity Prediction Tasks. In IEEE International Symposium on Multimedia, ISM 2021, Virtual Event, November 29 - December 1, 2021, pages 166-173. IEEE, 2021

2020

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Michael Vötter, Maximilian Mayerl, Günther Specht and Eva Zangerle: Recognizing Song Mood and Theme: Leveraging Ensembles of Tag Groups. In Working Notes Proceedings of the MediaEval 2020 Workshop. ceur-ws.org, 2020

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Maximilian Mayerl, Michael Vötter, Manfred Moosleitner and Eva Zangerle: Comparing Lyrics Features for Genre Recognition. In Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), pages 73-77. 2020.

2019

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Eva Zangerle, Ramona Huber, Michael Vötter and Yi-Hsuan Yang: Hit Song Prediction: Leveraging Low- and High-Level Audio Features. In Proceedings of the 20th International Society for Music Information Retrieval Conference 2019 (ISMIR 2019), pages 319-326. 2019

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Maximilian Mayerl, Michael Vötter, Eva Zangerle and Günther Specht: Language Models for Next-Track Music Recommendation. In Proceedings of the 31st GI-Workshop Grundlagen von Datenbanken, Saarburg, Germany, June 11-14, 2019., pages 15-19. 2019

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Michael Vötter, Eva Zangerle, Maximilian Mayerl and Günther Specht: Autoencoders for Next-Track-Recommendation. In Proceedings of the 31st GI-Workshop Grundlagen von Datenbanken, Saarburg, Germany, June 11-14, 2019., pages 20-25. 2019

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Maximilian Mayerl, Michael Vötter, Hsiao-Tzu Hung, Boyu Chen, Yi-Hsuan Yang and Eva Zangerle: Recognizing Song Mood and Theme Using Convolutional Recurrent Neural Networks. In Working Notes Proceedings of the MediaEval 2019 Workshop. ceur-ws.org, 2019.

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Hsiao-Tzu Hung, Yu-Hua Chen, Maximilian Mayerl, Michael Vötter, Eva Zangerle and Yi-Hsuan Yang: MediaEval 2019 Emotion and Theme Recognition task: A VQ-VAE Based Approach. In Working Notes Proceedings of the MediaEval 2019 Workshop. ceur-ws.org, 2019.