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 [log in to unmask] 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)
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