Jekyll2026-06-22T15:03:16+00:00https://musicallyembodiedml.github.io/feed.xmlMusically Embodied Machine LearningAHRC funded research project on musically embodied machine learningFirst LastnameRoland TR6S drum machine with the MEMLNaut2026-05-29T00:00:00+00:002026-05-29T00:00:00+00:00https://musicallyembodiedml.github.io/demo/controlling-fx-and-drum-parameters-usingControlling FX and drum parameters using NISPS

]]>First LastnameMemlnaut sax2026-05-27T00:00:00+00:002026-05-27T00:00:00+00:00https://musicallyembodiedml.github.io/demo/experimenting-with-grain-delays-todayExperimenting with grain delays today

]]>First LastnameMemlnaut dj fx2026-05-27T00:00:00+00:002026-05-27T00:00:00+00:00https://musicallyembodiedml.github.io/demo/in-vilnius-we-prototyped-a-djIn Vilnius we prototyped a DJ effects unit. Moving the joystick away from the centre fades in effects controlled by the neural net

]]>First LastnameMemlnaut and the Waldorf MicroQ2026-05-26T00:00:00+00:002026-05-26T00:00:00+00:00https://musicallyembodiedml.github.io/memlnaut/exploring-patches-with-midi-ccs-fromExploring patches with MIDI ccs from the neural net, with Linas @ Geeky Punks in Vilnius

]]>First Lastname2026-05-21T00:00:00+00:002026-05-21T00:00:00+00:00https://musicallyembodiedml.github.io/notes/memlnauts-superboothMemlnauts @ superbooth

]]>First LastnameSax vs Memlnaut2026-05-21T00:00:00+00:002026-05-21T00:00:00+00:00https://musicallyembodiedml.github.io/notes/rebuilding-the-sax-ahead-of-aRebuilding the sax ahead of a performance at NIME with Chris and Betty Accorsi

]]>First LastnameMEMLNauts Gig2025-09-12T00:00:00+00:002025-09-12T00:00:00+00:00https://musicallyembodiedml.github.io/events/gigs/RoseHillOctober 3rd 2025. 7pm-11pm The Rose Hill, Brighton, BN1 4JL £5 / £3

Tickets: www.ticketsource.co.uk/memlnauts

Emute Lab presents improvised performances from participants in the Musically Embodied Machine Learning project (MEML).

The MEMLNauts are finding new ways to be creative with machine learning, with impish algorithms driving newly customised instruments . Expect fractious brass, wayward woodwind, unruly vocal processing, and indecorous string feedback.

Embedded machine learning empowers musicians to find new performance approaches, by sharing control with often unpredictable and lively algorithms within the instrument. We will present performances with a variety of machine learning augmented instruments, in solo and group improvisations.

Rose Hill Gig Poster

Line up:

Tom Manoury

Bunty

Betty Accorsi

Andrea Martelloni

Luuma

Tom Manoury will be playing this augmented euphonium:

Bunty:

]]>First LastnameResearch Visit to the Intelligent Instruments Lab in Reykjavik2025-06-01T00:00:00+00:002025-06-01T00:00:00+00:00https://musicallyembodiedml.github.io/report/iilChris and Andrea recent spent a week in Iceland, visiting Thor Magnusson’s Intelligent Instruments Lab at the University of Reykjavik. Following our participatory design method, we spent the week working with Tom Manoury, exploring the augmentation of a euphonium using our MEMLNaut technology. We also working with Stefanos Vasilakis, who used the PAF synthesis MEMLNaut patch with external synth hardware. The week culminated in performances at Mengi, with the addition a duet with Andrea and Betty Accorsi on sax, and a Brain Dead Ensemble style trio with Thor Magnusson playing the Threnoscope, Chris playing MEMLNaut/Xiasri and Betty playing sax.

]]>First LastnameMEML @ CHIME 20242024-12-05T00:00:00+00:002024-12-05T00:00:00+00:00https://musicallyembodiedml.github.io/workshop/conference/chime-reportAt CHIME this year we ran a workshop and also shared some new instruments in the demo session. Here’s some documentation from the event.

]]>First LastnamePresentation to the Music Technology Group at Universitat Pompeu Fabra, Barcelona2024-12-05T00:00:00+00:002024-12-05T00:00:00+00:00https://musicallyembodiedml.github.io/presentation/upfmtgChris was visiting the Music Technology Group to examine Behzad Haki’s fascinating PhD research on generative realtime rhythmic accompaniment. He also gave a presentation on the MEML project. Here are the slides from the presentation:

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