We are delighted to announce an online seminar series as part of the
AHRC funded research network Datasounds, datasets and datasense:
Unboxing the hidden layers between musical data, knowledge and
creativity. Starting January 2022, we will host guest speaker on the
last Monday of the month on a range of topics relating to music, data
and the gaps between them. The talks will take place in the afternoon
(UK time). Abstracts, links for joining and specific time will be sent
before each seminar.
Feel free to email
o.ben-tal@kingston.ac.uk if you wish to receive
updates on the seminars or on the research network in general.
January 31 Renee Timmers (University of Sheffield) & Elaine Chew (IRCAM)
Renee Timmers' current research projects investigate ensemble
performance, in particular what visual and auditory nonverbal cues
musicians use to coordinate and communicate with each other during
performance.
Elaine Chew's research centers on the mathematical and computational
modeling of musical structures, with present focus on structures as
they are communicated in performance and in ECG traces of cardiac
arrhythmias.
February 28 Atau Tanaka (Goldsmiths University of London)
Atau Tanaka conducts research in embodied musical interaction. This
work takes place at the intersection of human computer interaction and
gestural computer music performance. He studies our encounters with
sound, be they in music or in the everyday, as a form of
phenomenological experience. This includes the use of physiological
sensing technologies, notably muscle tension in the electromyogram
signal, and machine learning analysis of this complex, organic data.
March 28 Blair Kaneshiro (Stanford University)
Blair Kaneshiro's research focuses on using brain and behavioral
responses to better understand how we perceive and engage with music,
sound, and images. Other research interests include music information
retrieval and interactions with music services; development and
application of novel EEG analysis techniques; and promotion of
reproducible and cross-disciplinary research through open-source
software and datasets.
April 25 Anna Xambo (De Montfort University)
Anna Xambo envisions pushing the boundaries of technology, design, and
experience towards more collaborative, egalitarian and sustainable
spaces, what I term intelligent computer-supported collaborative music
everywhere. My mission is to do interdisciplinary research that
embraces techniques and research methods from engineering, social
sciences, and the arts for creating a new generation of interactive
music systems for music performance and social interaction in
alignment with Computer-Supported Collaborative Work (CSCW)
principles.
May 30 Jeremy Morris (University of Wisconsin-Madison)
My research focuses on new media use in everyday life, specifically on
the digitization of cultural goods (music, software, books, movies,
etc.) and how these are then turned into commodified and sellable
objects in various digital formats. My book, Selling Digital Music,
Formatting Culture, focuses on the shared fate of the computing and
music industries over the last two decades and my recent co-edited
collections examine Apps (Appified, 2018) and Podcasting (Saving New
Sounds, 2021).
June 27 Psyche Loui ( Northeastern University)
Psyche Loui's research aims to understand the networks of brain
structure and function that enable musical processes: auditory and
multisensory perception, learning and memory of sound structure, sound
production, and the human aesthetic and emotional response to sensory
stimuli. Tools for this research include electrophysiology, structural
and functional neuroimaging, noninvasive brain stimulation, and
psychophysical and cognitive experiments
The Datasounds, datasets and datasense: Unboxing the hidden layers
between musical data, knowledge and creativity network aims to
identify core questions that will drive forward the next phase in
data-rich music research, focused in particular on creative music
making. The increased availability of digital music data combined with
new data science techniques are already opening new possibilities for
making, studying and engaging with music. This direction is only
likely to speed up upending many current practices, opening up
creative avenues and offering new opportunities for research. However,
the rapid technological progress with new techniques producing
surprising results in rapid succession, is often disconnected from the
knowledge and knowhow gained by musicians through creativity, practice
and research. By bringing together researchers and practitioners from
different underlying disciplines and with a wide range of expertise
the network will enable a better foundation for future research.
Performers, composers, and improvisers will contribute through
embodied knowledge and practice-based methods; researchers in
psychology will bring insights about cognitive, affective and
behavioural processes underpinning musical experience; and data
scientists will add analytical expertise as well as relevant theories,
methods and techniques. These will lead to significant conceptual
breakthroughs in data driven approaches and technologies applied to
music.
The network is lead by Oded Ben-Tal (Kingston University) in
partnership with Federico Reuben (York University), Emily Howard
(PRiSM, Royal Northern College of Music), Robin Laney (Open
University), Nicola Dibben (University of Sheffield), Bob Sturm (Royal
Institute of Technology, KTH, Sweden) and Elaine Chew (IRCAM)
