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Alexander Refsum Jensenius

Alexander Refsum Jensenius

Professor, Department of Musicology, University of Oslo

MishMash role: Director · WP1 , WP2 , WP3 , WP4 , WP5 , WP6 , WP7

Alexander Refsum Jensenius (BA, MA, MSc, PhD) is Professor of music technology at the University of Oslo. He works on the intersection of humans and machines, combining artistic and scientific research methods in creative ways.


MishMash Projects

Other projects

Latest results

Type

Book chapter

  1. Book chapter, 2026

    Rhythm and Residue: Vyping as Prompting Inside the Post-Discursive Interface

    Open access

    Enrique Encinas ; Andrew Morrison ; Alexander Refsum Jensenius ; Markéta Dolejšová ; John Hill

    Prompt engineering strategies emphasise clarity, specificity, and well-structured input, on the assumption that large language models (LLMs) require clean input to interpret user intent. But LLMs are pattern interpolators: they “absorb” noise through statistical reconstruction rather than strict symbol matching. Text-centric HCI has studied this tolerance for two decades without integrating it into prompt engineering as a resource. We introduce vyping as an intentional mode of prompting in which one types into LLMs at the speed of thought, without correction. We developed vyping through sustained first-person inquiry. It can be seen as a micro-practice inside a broader post-discursive turn in which meanings increasingly travel as rhythms and patterns through latent-space proximity rather than as precisely-formed symbols. The mismatch between current LLM interfaces and their (human) users has led to two common layers in implementation: (1) an orthographic residue at the interface (autocorrect, spellcheck, tidy-prompt guides), and (2) an impairment parse shadow at the training layer, a form of overalignment in which the model reads orthographic deviation as a sign that something is wrong with the user. Overall, we offer three attunements (ease, reach, and pulse) as alternatives to efficiency-first prompt engineering, and situate the practice within critical HCI traditions of seamful, frictional, and embodied interaction. The critique is structured around a seed prompt that suspends the impairment parse and makes vyping livable; its section headings are taken from the prompt’s own rules. A copy of the seed prompt is provided at the end.

  2. Book chapter, 2026

    The Perfect Wrong Note: Vyping and the Keyboard as Musical Interface for Human-LLM Interaction

    Enrique Encinas ; Alexander Refsum Jensenius

    Human interaction with large language models (LLMs) is commonly framed as information exchange, optimized for efficiency and correctness. This paper proposes a different framing: keyboard-as-instrument, where typing to an LLM becomes a form of musical practice. Drawing on the lineage of keyboard instruments, the action-sound framework, and the aesthetics of failure in jazz improvisation and glitch music, the paper introduces vyping (typing without looking) as a technique that treats degraded input as an expressive gesture. When a person vypes, inter-onset intervals and keystroke dynamics carry embodied information that the LLM can integrate, in a process closer to musical comping (responsive accompaniment) than to improvisation proper. Three artifacts (ll00mtube, clix-vibe, and KeyMeter) illustrate this approach, making the temporal and sonic dimensions of typing visible and audible. The paper argues that typos can function as grace notes: productive deviations that open new directions. It proposes reverence (nuance, grace, and respect) as a design orientation for human-AI interaction, while acknowledging the discomfort of caring for a tool entangled with extractive labor and concentrated corporate power.

Book of abstracts

  1. Book of abstracts, 2026

    DAIM 2026: Symposium on Digital and AI Musicology

    Open access, author's copy

    Olivier Lartillot ; Alexander Refsum Jensenius

    This report presents extended summaries of the presentations and discussions at the DAIM 2026 Symposium on Digital and AI Musicology, held on 8–9 June 2026 at the National Library of Norway and the University of Oslo. Organized by RITMO, the MishMash Centre for AI and Creativity, and the National Library of Norway, the symposium brought together the COST Action EarlyMuse and MishMash Work Package 6 on AI for Cultural Heritage. The contributions examine how computational methods and artificial intelligence can support the preservation, transcription, analysis, discovery, and interconnection of musical heritage. Topics include digital music collections, Optical Music Recognition, audio transcription, chant and Sámi yoik, musical similarity and pattern discovery, Linked Open Data, metadata standards, and sustainable research infrastructures. Discussions address scholarly validation, provenance, cultural context, and the rights of creators and communities. Compiled and edited by Olivier Lartillot, the report synthesizes presentation abstracts, slides, and recorded talks. It includes introductions to both days, presentation and panel summaries, links to related resources, contributor biographies, and the symposium programme, alongside a tribute to Eleanor Selfridge-Field.

Dataset

  1. Dataset, 2026

    micromotion: A Python toolbox for analysing human micromotion in motion time series

    Alexander Refsum Jensenius ; Finn Upham ; Agata Zelechowska ; Victor Evaristo Gonzalez Sanchez ; Dana Swarbrick ; Maham Riaz

    Software. One implementation of quantity of motion — the average speed of a body part, band-limited to 0.2-5 Hz, in millimetres per second — for optical marker data, body-worn accelerometers and force-plate centre of pressure, together with the readers, resampling rules, scaling measures and alignment methods that surround it.

More results in NVA…

Latest blog posts

From their own site, collected 16 October 2026. Nothing is copied here; the reading happens there.