Category Archives: Research

Where I write comments about things I think about and find interesting in relation to my research.

Self-playing guitars in Tampere

Earlier this year we were in Tampere with the self-playing guitars, and performed at the Tampere Conservatory. Here is a small video documentary made of the performance and with video interviews of the RITMO people involved.

And here is a recording of only the performance.

What tools do I use for writing?

Earlier today I was asked about what tools I use when writing. This is not something I have written about here on the blog before, although I do have very strong opinions on my own tools. I actually really enjoy reading about how other people work, so writing about it here may perhaps also be interesting to others.

Text editor: Atom

Most of my writing, whether it is e-mail drafts, meeting notes, or academic papers, is done in the form of plain text files. I use different text editors dependent on what computer/platform I am working on, and that is also one of the beauties of text files. They work everywhere. On my main laptop (running Ubuntu Studio), I primarily use Atom as my main text editor. This is mainly because it is cross-platform, has some plugins that are useful, and has excellent integration with Github.

Most of the time I write using markdown, which is just a structured way to write text files. The nice thing about markdown formatted text files, is that they can easily be converted to other formats using Pandoc. I often have to send off files as either PDFs or DOCX files, and this can easily be done with a terminal command such as:

pandoc file.txt -o file.pdf 

Yes, it is a nerdy way of writing things, but working in a text editor (as opposed to a word processor) is just so much quicker for many things. I use quite a lot of advanced query-replace functions, for example, and then regular expressions are useful. I also like to be able to do multiline editing.

Academic writing: Overleaf

I usually start my academic writing with notes in markdown, but as soon as I start to get into the proper writing mode, I convert into LaTeX. This is also a text-based format, but with a slightly more complex (and also more powerful) syntax than markdown.

Since most of my academic writing these days is collaborative, I almost only work in the web-based LaTeX editor Overleaf. This editor makes it possible for multiple users to work on the same document, and it also handles the compiling into PDFs very nicely. Being a web app, you don’t have to install LaTeX locally on your own computer. This makes it much easier for people to get started with LaTeX than it used to be only a few years ago.

Academic references: Zotero

Zotero is my current reference manager. It is not perfect, but I like that it is cross-platform (and by that I mean Windows, OSX, and Linux), it has a web interface, and it synchronizes between systems. There is a connection from Zotero to Overleaf, but I have found this to be somewhat shaky. So most of the time, I just export a BibTeX file of my complete library from Zotero, and import that .bib file in Overleaf.

Other collaborative writing: Google Docs

When I am writing non-academic texts with others, such as administrative documents, reports, and so on, I typically use Google Docs. I have been using it for several years now, and it really shines when it comes to collaborative writing and editing. I try Office 365 from time to time, but it just cannot compare to the trouble-free collaboration I experience in Google Docs.

Word processor: LibreOffice

When I have to use a normal word processor, it is usually LibreOffice. I never start writing in LibreOffice myself, so this only happens when someone sends me a .docx file that they want me to look at. Fortunately, LibreOffice handles .docx files well most of the time. So I am able to edit documents using “track changes” and send them back to people using MS Word.

In those few cases where LibreOffice does not manage to handle the .docx documents I receive, I connect to a remote desktop at the university and fire up MS Word. This is typically when there are some weird macro functions in the document, or some strange fonts. Fortunately, this happens only once in a while.

Summing up

All in all, I am quite happy with my current set of tools. Relying on text files has worked well for me for many years now. They are also the most future-proof solution I can think of. My software tools will continuously be replaced, but I am sure that plain text files will be around for a long time.

NIME publication and performance: Vrengt

My PhD student Cagri Erdem developed a performance together with dancer Katja Henriksen Schia. The piece was first performed together with Qichao Lan and myself during the RITMO opening and also during MusicLab vol. 3. See here for a teaser of the performance:

This week Cagri, Katja and myself performed a version of the piece Vrengt at NIME in Porto Alegre.

We also presented a paper describing the development of the instrument/piece:

Erdem, Cagri, Katja Henriksen Schia, and Alexander Refsum Jensenius. “Vrengt: A Shared Body-Machine Instrument for Music-Dance Performance.” In Proceedings of the International C Onference on New Interfaces for Musical Expression. Porto Alegre, 2019.


This paper describes the process of developing a shared instrument for music–dance performance, with a particular focus on exploring the boundaries between standstill vs motion, and silence vs sound. The piece Vrengt grew from the idea of enabling a true partnership between a musician and a dancer, developing an instrument that would allow for active co-performance. Using a participatory design approach, we worked with sonification as a tool for systematically exploring the dancer’s bodily expressions. The exploration used a “spatiotemporal matrix,” with a particular focus on sonic microinteraction. In the final performance, two Myo armbands were used for capturing muscle activity of the arm and leg of the dancer, together with a wireless headset microphone capturing the sound of breathing. In the paper we reflect on multi-user instrument paradigms, discuss our approach to creating a shared instrument using sonification as a tool for the sound design, and reflect on the performers’ subjective evaluation of the instrument.

NIME publication: “NIME Prototyping in Teams: A Participatory Approach to Teaching Physical Computing”

The MCT master’s programme has been running for a year now, and everyone involved has learned a lot. In parallel to the development of the programme, and teaching it, we are also running the research project SALTO. Here the idea is to systematically reflect on our educational practice, which again will feed back into better development of the MCT programme.

One outcome of the SALTO project, is a paper that we presented at the NIME conference in Porto Alegre this week:

Xambó, Anna, Sigurd Saue, Alexander Refsum Jensenius, Robin Støckert, and Øyvind Brandtsegg. “NIME Prototyping in Teams: A Participatory Approach to Teaching Physical Computing.” In Proceedings of the International Conference on New Interfaces for Musical Expression. Porto Alegre, 2019.

Anna Xambó presents the paper “NIME Prototyping in Teams: A Participatory Approach to Teaching Physical Computing” at NIME 2019.


In this paper, we present a workshop of physical computing applied to NIME design based on science, technology, engineering, arts, and mathematics (STEAM) education. The workshop is designed for master students with multidisciplinary backgrounds. They are encouraged to work in teams from two university campuses remotely connected through a portal space. The components of the workshop are prototyping, music improvisation and reflective practice. We report the results of this course, which show a positive impact on the students on their intention to continue in STEM fields. We also present the challenges and lessons learned on how to improve the teaching and delivery of hybrid technologies in an interdisciplinary context across two locations, with the aim of satisfying both beginners and experts. We conclude with a broader discussion on how these new pedagogical perspectives can improve NIME-related courses.

RaveForce: A Deep Reinforcement Learning Environment for Music Generation

My PhD student Qichao Lan is at SMC in Malaga this week, presenting the paper:

Lan, Qichao, Jim Tørresen, and Alexander Refsum Jensenius. “RaveForce: A Deep Reinforcement Learning Environment for Music Generation.” Proceedings of the Sound and Music Computing Conference. Malaga, 2019.

The framework that Qichao has developed runs nicely with a bridge between Jupyter Notebook and SuperCollider. This opens for lots of interesting experiments in the years to come.


RaveForce is a programming framework designed for a computational music generation method that involves audio sample level evaluation in symbolic music representation generation. It comprises a Python module and a SuperCollider quark. When connected with deep learning frameworks in Python, RaveForce can send the symbolic music representation generated by the neural network as Open Sound Control messages to the SuperCollider for non-realtime synthesis. SuperCollider can convert the symbolic representation into an audio file which will be sent back to the Python as the input of the neural network. With this iterative training, the neural network can be improved with deep reinforcement learning algorithms, taking the quantitative evaluation of the audio file as the reward. In this paper, we find that the proposed method can be used to search new synthesis parameters for a specific timbre of an electronic music note or loop.