Self Organizing Maps for the Visual Analysis of Pitch Contours
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We present a novel interactive approach for the visual analysis of intonation contours. Audio data are processed algorithmically and presented to researchers through interactive visualizations. To this end, we automatically analyze the data using machine learning in order to find groups or patterns. These results are visualized with respect to meta-data. We present a flexible, interactive system for the analysis of prosodic data. Using real-world application examples, one containing preprocessed, the other raw data, we demonstrate that our system enables researchers to interact dynamically with the data at several levels and by means of different types of visualizations, thus arriving at a better understanding of the data via a cycle of hypothesis generation and testing that takes full advantage of our visual processing abilities.
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SACHA, Dominik, Yuki ASANO, Christian ROHRDANTZ, Felix HAMBORG, Daniel A. KEIM, Bettina BRAUN, Miriam BUTT, 2015. Self Organizing Maps for the Visual Analysis of Pitch Contours. 20th Nordic Conference of Computational Linguistics. Vilnius, 11. Mai 2015 - 13. Mai 2015. In: BEÁTA MEGYESI, , ed.. Proceedings of the 20th Nordic Conference of Computational Linguistics : NODALIDA 2015 ; May 11–13, 2015 in Vilnius, Lithuania. ACL Anthology, 2015, pp. 181-189. eISSN 1650-3740. ISBN 978-91-7519-098-3BibTex
@inproceedings{Sacha2015Organ-31874, year={2015}, title={Self Organizing Maps for the Visual Analysis of Pitch Contours}, isbn={978-91-7519-098-3}, publisher={ACL Anthology}, booktitle={Proceedings of the 20th Nordic Conference of Computational Linguistics : NODALIDA 2015 ; May 11–13, 2015 in Vilnius, Lithuania}, pages={181--189}, editor={Beáta Megyesi}, author={Sacha, Dominik and Asano, Yuki and Rohrdantz, Christian and Hamborg, Felix and Keim, Daniel A. and Braun, Bettina and Butt, Miriam} }
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