salle Nono
Transmission
Software Training
Sensors, Interfaces, and Interactive Machine Learning for Music
Master Sensors to Program Interactive Sound and Music Systems
Objectives
Upon completion of this training program, participants will have acquired the theoretical and practical notions for realization of interactive sound and music systems using R-IoT sesnsors (9-axis sensor with accelerometres, WIFI), as well as pattern-recognition systems. Programming interfaces such as the Arduino or R-IoT will also be addressed
Public
Composers, musicians, performers, teachers, designers
Prerequisites
- Participants must be able to justify a good knowledge of Max and its environment: completion and understanding of the basic Max tutorials (Max Basisc tutorials 1 à 11, 14 à 22, Max Data tutorials 1 et 2, MSP tutorials, MSP Basics tutorials 1 à 5, MSP Panning tutorials 1 à 3, MSP Analysis tutorials 1 à 2, MSP Delay tutorials 1 à 3 et 6) or to have followed the Max Initiation course.
- Possess a good knowledge of technical English vocabulary and terms used in common audio software.
- Mastery of the basic functions of a Macintosh computer (use of a keyboard and mouse, create and manage files and folders, use menus, launch an application).
- A good knowledge how to use of an audio sequencer (Ableton Live, Reaper, Protools, Logic Pro...) is also recommended.
- Basic mathematical concepts will facilitate understanding: integers, rational and decimal numbers, sums, subtractions, multiplications, divisions, absolute value, study of simple functions.
Training Period and Organization
24 hours of training. Tuesday-Friday, May 19-22, 2026. 10am-1pm/2:30pm-5:30pm
10 students maximum
In the event that IRCAM cannot physically welcome students for a program that requires face-to-face instruction, the program will be cancelled.
Program
Some details of the training program are subject to revision as the software on which it is based evolves.
Tuesday
| Morning | Overview of different types of sensors, interfaces, and suppliers. The particular case of wireless sensors Hands-on exercises: use the programming environments Arduino. |
| Afternoon | Hands-on exercises : master the basics of programming in Arduino, first simple examples of coding, uploading code towards the Arduino and R-IoT interfaces. |
Wednesday
| Morning | Recuperation and processing of sensor data in Max (Arduino and R-Iots) Filtering (average, median filter, low pass filter) and normalization |
| Afternoon | Implementation of a mapping system Direct use of sensor data with simple sound processes. Synthesis control, playback of sound files |
Thursday
| Morning | Hands-on exercises: create a sonification system: using the R-IoT Sensor, recuperation of data and sonification in Max |
| Afternoon | Introduction to the MuBu library and Gesture follower. |
Friday
| Morning | Theory: introduction to "machine learning" with the Mubu for Max library allowing advanced applications for gesture and motion recognition. Presentation of examples of use in sonic and artistic projects (performative art) |
| Afternoon | Hands-on exercises: produce a system with sensors connected to the R-IoT interface, learning, and recognition in Max with MuBu |
Educational Resources and Techniques
- Classroom equipped with computers with all the necessary software installed, headphones, and MIDI keyboards
- Participants will be provided with kits that include an R-IoT card.
The R-IoT module is part of the training fee (valued at €99 excluding VAT). - Class Format: training alternates between presentations, explanations on theory, studying examples to analyze, and hands-on exercises.
- Didactic Materials: video-projected presentations and PDF documents.
Supervision
- Welcome the first day of training beginning at 9:45am
- Attendance controlled: signature of an attendance sheet required every morning and afternoon
- A certificate at the end of the program is given to each participant with the results of the exam
.Assessment
- Assessment of knowledge will take the form of hands-on exercises throughout the training.