AES Technical Committee

Machine Learning & Artificial Intelligence

Chair:    Gordon Wichern      Send Email
Vice Chair:    Christian Uhle      Send Email
Vice Chair:    Brecht De Man      Send Email

The Technical Committee on Machine Learning and Artificial Intelligence (TC-MLAI) focuses on applications of machine learning and artificial intelligence in audio, with discussions on topics such as: best practices, data, licensing, social and cultural aspects, technical innovations, and ethics. The goal of the committee is to drive discussion and exchange information by organizing and disseminating workshops, symposia, tutorials, and technical documents. The TC-MLAI acts as a point of contact and a bridge to other AES technical committees, the AES community at large, and other organizations involved in ML and AI for audio.


Areas of Concentration

  • Artificial intelligence and creativity
  • Ethical and social considerations of AI applications.
  • Best practices for data and metadata handling, e.g. data collection, labeling, and storage.
  • Best practices for workflows, e.g. when updating, deploying and assuring quality of trained models.
  • Licensing issues for data, pretrained models, and software implementations (external libraries)
  • Aspects of evaluation, both objective and perceptual
  • Explaining and understanding decisions of data driven systems
  • Security and robustness
  • Machine Learning and Artificial Intelligence Algorithms
  • Documentation of evolution and history of ML and AI
  • Applications in:
  • Content analysis
  • Source separation
  • Music and sound generation
  • Automated and assistive audio production
  • Digital audio effects
  • Repair, restoration, and enhancement
  • Educational tools
  • Automatic speech recognition
  • Speech synthesis
  • Spatial audio
  • Audio coding
  • Systems diagnostics

Current Areas Of Work

  • Papers sessions
  • Workshops
  • Symposiums
  • Identify trends


Meeting Report:

These documents do not necessarily express the official position of the AES on the issues discussed at these meetings, and only represent the views of committee members participating in the discussion. Any unauthorized use of these publications is prohibited. Authorization must be obtained from the Executive Director of the AES: Email, Tel: +1 212 661 8528, Address: 551 Fifth Ave., Suite 1225, New York, New York 10176, USA.

2022-11-1     TC MLAI Meeting Minutes 2022-10-24
Description: TC MLAI Meeting Minutes 2022-10-24

2022-6-2     TC MLAI Meeting Minutes 2022-06-01
Description: TC MLAI Meeting Minutes 2022-06-01

2021-11-22     TC MLAI Meeting Minutes 2021-10-19
Description: TC MLAI Meeting Minutes 2021-10-19

2021-6-7     TC MLAI Meeting Minutes 2021-06-02
Description: TC MLAI Meeting Minutes 2021-06-02


Other:

2022-11-11     AES 153 - Teaching AI to hear like we do: psychoacoustics in machine learning slides
Description: Slides from the first in-person workshop organized by TC-MLAI


Committee Members

 Brent Harshbarger  Gerald Schuller  Gordon Reid 
 Marina Bosi  David Andrews  Steve Hutt 
 Anibal Ferreira  Jamie Angus  Jean-Marc Jot 
 J. Keith McElveen  Michelle Daniels  Christian Uhle 
 David Prince  Shahan Nercessian  Julian Parker 
 Jordan Juras  Jonathan Wyner  M. Lefford 
 Ronny Andersson  Jan Skoglund  Renato de Castro Rabelo Profeta 
 Christos Chousidis  Brecht De Man  Dave Moffat 
 Christian Steinmetz  Gordon Wichern  Mikus Salgravis 
 Andy Sarroff  Harry Andrews  Dylan Flesch 
 Joey Stuckey  Rebecca Fiebrink  Matthew Pitkin 
 Alexander Wankhammer  Joseph Colonel  Jorge Garcia 
 Angeliki Mourgela  Daniel Turner  Robert Werner 
 Flavio Everardo 

To request membership in this Technical Committee please email the Chair by using the link above.

AES - Audio Engineering Society