Kolloquium: Man-Machine Creative Interaction and Improvisation
- Datum: 14.05.2018
- Uhrzeit: 15:00
- Vortragende(r): Shlomo Dubnov
- Ort: Max-Planck-Institut für Bildungsforschung, Lentzeallee 94, 14195 Berlin
- Raum: Großer Sitzungssaal
- Gastgeber: Forschungsbereich Entwicklungspsychologie
- Kontakt: email@example.com
The Center for Lifespan Psychology at the Max Planck Institute for Human Development, led by Prof. Ulman Lindenberger, cordially invites all interested to attend its colloquium
Shlomo Dubnov, University of California, San Diego (USA)
Man-Machine Creative Interaction and Improvisation
Having worked for many years in computer modeling of music and improvisation with computers, Shlomo Dubnov and his team have gained some valuable insights about various aspects of human creative interaction with a machine. Their research is based on data-driven modeling of music that could be used both for analysis and generation. Research topics in this field include, among others, the use of machine learning algorithms to create variations in a particular style, estimation of the level of surprisal (on unpredictability) in music, and understanding of how listeners and performers interact and react to creative man-machine situations.
In the talk Shlomo Dubnov will present two main techniques that they have been developing: music information dynamics analysis, and generative machine learning of musical style. One of the difficulties in statistical modeling of music is the large memory requirement for identification of salient musical elements. He will describe the Variable Memory Oracle (VMO) toolkit that uses string matching and compression to analyze and generate music, with applications to motif discovery, segmentation and query based generation, as well as applications for gesture recognition and other time series data.
A central challenge in improvisation systems is establishing a meaningful and engaging interaction between man and machine. Due to the lack of clear measures of quality for such interaction, variants of Turing test and self reported Flow experience are often used to evaluate such systems. Considering the growing body of literature on social interaction using physiological measurements, they hope also to gain new understanding of man-machine interaction by applying measures of information transfer between human and machine generated signals in dynamic settings.
Shlomo Dubnov is a Professor in UCSD Music Department in the Computer Music area and is an Affiliate Faculty in Computer Science and Engineering Department. He graduated from the Jerusalem Music Academy in composition and holds a PhD in Computer Science from the Hebrew University, Jerusalem. He is a graduate of the prestigious IDF Talpiot program, he served as a researcher at the Institute for Research and Coordination of Acoustics and Music (IRCAM) in Paris, and headed the multimedia track for the Department of Communication Systems Engineering at Ben-Gurion University, in Israel. Dr. Dubnov currently serves as the Director of the Qualcomm’s Institute’s Center for Research in Entertainment and Learning (CREL) at UCSD.