Search research publications and outputs

  1. 2019
  2. Algorithmic music curation in audio branding: Commercial and critical perspectives on an international research and innovation project

    Edwards, J. & Egermann, H. W., 2019, Algorithmic Music: Value, Creativity and Artificial Intelligence A One-day Symposium.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  3. An Interactive Spatial Audio Experience for Children with Autism Spectrum Disorder

    Johnston, D. I., Egermann, H. W. & Kearney, G. C., 2019, Proceedings of the 2019 AES International Conference on Immersive and Interactive Audio. Audio Engineering Society

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  4. 2018
  5. Smartphone-Assessed Movement Predicts Music Properties: Towards Integrating Embodied Music Cognition into Music Recommender Services via Accelerometer

    Irrgang, M., Steffens, J. & Egermann, H. W., 28 Jun 2018, Proceedings of the 5th International Conference on Movement and Computing, MOCO 2018. ACM Digital Library, 4 p. 31

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  6. 2017
  7. Predicting Musical Meaning in Audio Branding Scenarios

    Herzog, M., Lepa, S., Steffens, J., Schoenrock, A. & Egermann, H. W., 31 Jul 2017, Proceedings of the 25th Anniversary Conference of the European Society for Cognitive Science of Music, Ghent, Belgium, 31 July – 4 August 2017. Van Dyck, E. (ed.). ESCOM, p. 75-79 5 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  8. Development and Evaluation of an Interface with Four-Finger Pitch Selection

    von Coler, H., Treindl, G., Egermann, H. W. & Weinzierl, S., 11 May 2017, Proceedings of the 142nd AES Convention - Audio Engineering Society. Audio Engineering Society, p. 1-8 8 p. 9792

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  9. High-Level Chord Features Extracted From Audio Can Predict Perceived Musical Expression

    Steffens, J., Lepa, S., Schoenrock, A., Herzog, M., Peeters, G. & Egermann, H. W., 2017, Extended abstracts for the Late-Breaking Demo Session of the 18th In- ternational Society for Music Information Retrieval Conference, Suzhou, China, 2017. 2 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  10. 2016
  11. Spreadsheets as user interfaces

    Dix, A., Cowgill, R., Bashford, C., Mcveigh, S. & Ridgewell, R., 7 Jun 2016, Proceedings of the International Working Conference on Advanced Visual Interfaces. Buono, P., Lanzilotti, R. & Matera, M. (eds.). New York: Association for Computing Machinery (ACM), p. 192-195 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  12. 2015
  13. Auditive and Audiotactile Music Perception of Cochlear Implant Users

    Papadogianni-Kouranti, M., Egermann, H. & Weinzierl, S., 2015, Fortschritte der Akustik: Tagungsband d. 41. DAGA. Becker, S. (ed.). Oldenburg: Deutsche Gesellschaft für Akustik, p. 1203-1205 3 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  14. Gesture-sound causality from the audience's perspective: investigating the influence of mapping design on the reception of new digital musical instruments

    Emerson, G., Förstel, A. & Egermann, H., 2015, Tagungsband Jahrestagung der deutschen Gesellschaft für Musikpsychologie. Kreutz, G. (ed.). Oldenburg, Germany: Deutsche Gesellschaft für Musikpsychologie, p. 1-2 2 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  15. Learning Statistical Regularities of a Simple Musical 'Genre': The Case of Radio Station Jingles

    Müllensiefen, D., Egermann, H. & Burrows, S., 2015, Proceedings of the European Conference on Data Analysis. Lausen, B. (ed.). Colchester: Gesellschaft für Klassifikation, p. 1 1 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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