Following the class Basics for ATIAM, the training continues with Musical Acoustics, Musical Signal Processing and Computer-Music. At the same time, students work together in small groups, combining several scientific domains in a single research project applied to music in the class Projects and Musical Applications. These projects are the students’ first research experiences in the fields explored during the program. Students also follow a class on their future careers with a focus on the specificities offered by the ATIAM program. During this class, students work on their scientific English vocabulary as well as adapting to working conditions in their chosen domain. The year ends with a 5-month internship in a professional research laboratory.


  Moreno Andreatta
  6 ects

This teaching unit aims to provide the basics enabling the different teaching units to fully develop, as well from a scientific point of view as from the general knowledge of Twentieth-Century music and musicology.
The first part provides an introduction to XXth Century music and musicology, by focusing in particular on Computational Music Analysis.
The second part of this unit provides a harmonization of different levels with respect to acoustics, signal processing and informatics:
– Acoustics: the acoustical part of FPA concerns:
(1) basic linear acoustics, Helmholtz resonator, 1D wave guides
(2) 1 or 2 degree(s) of freedom oscillator, vibrating string equation
(3) loudspeaker functioning and modeling.
– Signal processing: the first part of this course introduces the fundamentals of signal processing (Fourier transform, spectral observation, sampling, filtering, Z-transform, filter synthesis). The second part deals with random processes (strict and wide sense stationarity, filtering, linear prediction, parametric and non-parametric estimation).
– Informatics: on this 15-hour course we will widely cover on a fast and general way multiples informatic areas. Main idea is that the student can go deeper over a self-interest area which will be shortly presented during the class. Within the topics that will be exposed are: Calculability, Complexity, Programming languages (particularly functional programing and its subjacent model the lambda-calcul). Besides we will expose some others concurrent models which are useful for the interactive systems modeling. We will try to give examples about all this concept applied to the music.

  Jean-Loïc Le Carrou
  6 ects

The aim of this UE is to develop a good competence on the main scientific tools of musical acoustics, by enabling a deep understanding of musical instruments, going from physical acoustics and vibrations problems. A good knowledge of some theoretical tools in acoustics (such as frequency/temporal response, Green functions, etc.) coupled with an understanding of dissipative mechanisms should provide the tools for studying  the oscillation systems of musical instruments the coupling of the different elements which structure it, the control of the musical instrument by the musician, the diffusion of sound in a concert hall.

  Roland Badeau
  6 ects

This course introduces various tools for signal processing and representation (filter synthesis, resampling, short-time Fourier transform, filter banks), analysis-transformation-synthesis of music signals (phase vocoder, additive synthesis, source/filter models), nonlinear signal and system modeling (Volterra series) as well as various musical applications (estimation of musical structures, multipitch estimation, high-resolution spectral analysis, automatic music transcription and source separation by means of nonnegative matrix factorization).

  Philippe Esling
  6 ects

The aim of this unit is to develop a sound knowledge of both computer-aided tools but also the romantic view on informatics which are relevant to music. This perspective embeds machine learning, symbolic representations, lambda calculus and programming languages. The student will discover different aspects of computer programming for music, through five major axes:
– Algorithmics study symbolic structures, state machine and automata theory, music analysis and generation up to embedded systems in Arduino.
– Digital audio production (Ableton Live), reactive audio programming (MaxMsp and PureData), synthesizer software programmation (Max4Live and VST programming)
– Artificial Intelligence and machine learning will be exhaustively studied through eight sessions covering neural networks, kernel methods up to the latest variational inference and deep learning
– Control theory will introduce the notions of linear and optimal systems that can be applied for the active control of musical instruments
– Web audio will cover the basics to perform music processing over distributed devices and handle different real-time constraints in performance

  Benoit Fabre
  6 ects

This teaching unit proposes some practical applications of acoustics, signal processing and computer science to the musical field. Its main objective is to enable the student to integrate the different competences acquired within the different scientific domains by applying them to a musical problem. Based on the project pedagogy, this unit will help students to work in a collective way by developing their competences in a specific personal direction. The contents of the projects are selected by the pedagogical staff in order to facilitate the mutual collaborations around recent research domains (see the list of selected projects on the right).


Carlos Agon and Isabelle Viaud-Delmon
3 ects

This module will help ATIAM students to enhance their academic career and to build their professional project. Writing and presentation techniques based on an analysis of the target audience will be addressed. Visits to laboratories and presentation sessions of the professions (academic and non-academic sectors) related to the ATIAM master’s degree are proposed.
– What to do with your Master?
– How to write a Curriculum Vitae? How to prepare an interview?
– How to write the Master Dissertation?
– How to write a scientific article?
– Visit to the main affiliated research Labs: LAM & Télécom Paris, visit to LMA (Marseille)

3 ects
24 ects