Technology | Diversity | Democracy

Telematic Music: What to play

Original Members of the Scratch Orchestra and new collaborators play Nature Study Notes

Previously, we’ve talked about some of the musical implications of playing via Jitsi Meet. These included lag (aka delay), compression (aka distortion) and levels (aka headroom / peaking). This means that we will be unable to synchronise, our sounds will be altered and we need to be aware of leaving space for others to play. This is a challenge, but it implies new possibilities and ways of working.


Your group might experiment to see what kinds of sounds and groupings work well for telematic music. You can use video or text to cue each other. You can figure out what you’re going to do ahead of time in as much or as little detail as you’d like. Be aware that unexpected things can happen, especially when relying on the internet. Writer Simon Yuill notes that practising this kind of music is in some ways like practising football. Performers can plan for uncertainly and improvisation by considering and practising how they might react to certain scenarios.

Here are some other ways that people have approached this type of music and what we can learn from them.

Network Music

Any music that has (computer) networking as an intrinsic part of it is called “network music”. Telematic music is just one kind of network music. It may be useful to discuss how others have worked with networks in the past.

The first ever telematic concert was put on by a computer music band called The Hub in 1987. The Hub got its name from a piece of networking equipment very similar to an internet router. Networking was an important part of most of their pieces and a lot of their pieces explored the musical implications of networks – there’s more information about their work here: http://crossfade.walkerart.org/brownbischoff/.

One of their best-known pieces is called Stuck Note, by Hub member Scot Gresham Lancaster. In that piece, every member of the band came up with a sound they were going to play. Then, to control the sound, they had two parameters: the amplitude and an X-factor. The X-factor could control any aspect(s) of the sound: the pitch, the sound quality or any combination of factors.

To further shake things up, each member shared their controls with every other member. So if John and I were playing this piece together, I would have access to my own amplitude and X-factor and also John’s. And John would also have access to mine and his. If I don’t like his sound I can turn it down, or if I do like it, I can turn it up and vice versa.

The result is not what you’d expect. There is as far as I am aware no free streaming version of the album , but it is available on some paid music services: https://www.tzadik.com/index.php?catalog=8050-3.

This piece isn’t one you could do with Jitsi, but it does show that it might be helpful to think about what using a network implies. There’s a chat feature in Jitsi and a way to send private messages to particular users. Would it be helpful to use that in your music? (Be careful of typing noise if you’re using the internal mic – or make the typing part of your sound.)

Stuck Note is also interesting because the score doesn’t say anything about what sounds to play. It just says how to get ready. Bands covering this piece usually try things out for a while and develop a loose performance score – based on experimentation, they learn each other’s sounds and get an idea for how to start and end. Many bands leave the middle open, to give room to improvise.

Improvising

Improvising has always been a part of music making. To pick some western examples, early medieval musicians improvised along with chanting in a practice that eventually became polyphony. Classical musicians improvise in orchestral pieces by playing short sections called cadenzas. The type of music we now call “free improvisation” has multiple roots, including European experimentalism and American jazz.

Scratch Music

One important European groups was the Scratch Orchestra. One of their founders, Cornelius Cardew, described himself as a “square” classically trained musician. Like many with such training, he found it difficult to improvise. Many people have a hard time being spontaneous. Cardew and the Scratch Orchestra tried to find ways to lead themselves to greater musical freedom.

One such work was called Treatise. It’s a long graphic score that has music-like symbols and shapes in it, but is not traditional sheet music. The people playing it need to try to figure out what to play by imagining what sounds the shapes imply or thinking of things it reminds them of. Early on, they looked at the score, figured out what to play and wrote it down. Later, they were able to use the score directly. Monoskop has more on Cardew and Treatise: https://monoskop.org/Cornelius_Cardew.

It may seem like a contradiction to have a score for free improvisation, but a score can help create structure and give people ideas. This is especially evident in text scores. American composer Pauline Oliveros called some of her scores “algorithms”. Here, again, Scratch Music is influential.

Nature Study Notes is a collection of text-based Scratch scores. Unusually, these contain an anti-copyright notice at the start saying anyone can copy and add to the collection. (You can find a copy here: http://intuitivemusic.dk/iima/sonsn.pdf.) This has been hugely influential in the Free Software movement (which Jitsi comes from) and in Hack spaces, especially music hack spaces.

One short score in Nature Study Notes, by Carole Finer, says to play the cover of the Evening Standard Newspaper as if it were music notation.

Another score that might work well for Jitsi is HSIR8 (all the scores are titled by codes) in which players compete to play the shortest, quietest sound, or CCAR17 where players take turns soloing and accompanying. For Jitsi players, accompanists would need to be certain to leave enough amplitude space for the soloist. Keeping groups small would help with this.

Free Jazz

Jazz music has a long tradition of free-improvised solos and virtuosic musicians. It also has algorithmic scores. George Lewis, a composer and trombonist, is a pioneer of computer music, developing several systems to accompany and collaborate with soloists. Computer music is necessarily made of rules and instructions – algorithms, which dictate what the system should do based on input. This doesn’t mean that the soloist or even the programmer can exactly predict what’s going to happen. Behaviour emerges from the rules. Lewis conceives of this as the program having its own sound, as in its own narrative or personality. His best known computer piece, Voyager from 1987, is for a soloists and an interactive orchestra. You can listen to a recording here: https://www.youtube.com/watch?v=hO47LiHsFtc

Anthony Braxton also has worked to create logics for performance. These systems allow him to explore aesthetic and musical ideas. For example, his Language Music explores different kinds of sounds one could use for improvisation. Players might all play long sounds or legato sounds. A conductor can give hand signals to indicate that players should move from one language to another. In some of his large ensemble concerts, they might be more than one conductor who could indicate to a group of players that they should break off into a separate language instruction. Performers can also take opportunities to recruit their neighbours into ad-hoc sub-ensembles and also explore languages. The shared systems give conductors and performers a flexibility that helps improvisation. Similar to the Scratch Orchestra, players in a Braxton concert may play more than one piece at a time.

Share your scores!

If you or your group want to share a score that you’ve developed for Jitsi, leave a comment. I’ll post a few such scores in a few weeks.