[apologies for cross-posting, please circulate this call widely]
First AES International Conference on Artificial Intelligence and Machine
Learning for Audio (AIMLA 2025), London, Sept. 8-10, 2025, Call for
contributions
The Audio Engineering Society invites audio researchers and practitioners, from
academia and industry to participate in the first AES conference dedicated to
artificial intelligence and machine learning, as it applies to audio. This 3
day event, aims to bring the community together, educate, demonstrate and
advance the state of the art. It will feature keynote speakers, workshops,
tutorials, challenges and cutting-edge peer-reviewed research.
The scope is wide - expecting attendance from all types of institutions, inc.
academia, industry or pure research, with diverse disciplinary perspectives -
but tied together by a focus on artificial intelligence and machine learning
for audio.
Original contributions are encouraged in, but not limited to the following
topics:
*
Intelligent Music Production
*
Knowledge Engineering Systems
*
Automatic Mixing / Remixing / Demixing / Mastering
*
Differentiable Audio Effects
*
Audio and Music Generation
*
Generative models for audio
*
Deep Neural Audio Codecs
*
Neural Audio Synthesis
*
Text-to-audio generation
*
Instrument models
*
Speech and Singing voice synthesis
*
AI for sound design
*
Differentiable Synthesisers using DDSP and other neural models
*
Representation Learning
*
Fingerprinting using deep learning
*
Transfer Learning
*
Domain Adaptation
*
Transfer of musical composition and performance characteristics including,
timbre, style, production, mixing and playing technique
*
Real-time AI For Audio
*
Model Compression (Quantization, Knowledge Distillation)
*
Efficient Model Design and Benchmarking
*
Real-time inference frameworks in software and hardware
*
Applications of AI in Acoustics and Environmental Audio
*
Machine learning and AI models for acoustic sensing
*
Deep learning for acoustic scene analysis
*
Deep learning for localisation in noisy and reverberant environments
*
Binaural processing with AI or ML
*
Source and scene classification
*
Source separation, source identification and acoustic signal enhancement
*
AI-driven distributed acoustic sensor networks
*
Control and estimation problems in physical modelling
*
AI-based perception models inspired by human hearing
*
Application of AI to wave propagation in air, fluids and solids
*
AI Ethics for Audio and Music
*
AI-Generated Music and Creativity
*
Intellectual Property in AI-Composed Music
*
AI in Environmental Sound Monitoring
*
Cultural Appropriation in AI Music
*
Environmental Impact of Audio Data Processing
Call for Tutorials
We are seeking proposals for 120-minute hands-on tutorials on the conference
topics. The proposal should include a title, an abstract (60-120 words), a list
of topics, and a description (up to 500 words). Additionally, the submission
should include presenters' names, qualifications, and technical requirements
(sound requirements during the presentation, such as stereo, multichannel,
etc.). We encourage tutorials to be supported by an elaborate collation of
discussed content and code to support learning and building resources for a
given topic.
Important dates:
Deadline for tutorial proposals: 15th Nov 2024
Accepted sessions notified by: 24th Jan 2025
Call for Challenges
The AES AI and ML for Audio conference promotes knowledge sharing among
researchers, professionals, and engineers in AI and audio. Special Sessions
include pre-conference challenges hosted by industry or academic teams to drive
technology improvements and explore new research directions. Each team manages
the organization, data provision, participation instructions, mentoring,
scoring, summaries, and results presentation. Challenges are selected based on
their scientific and technological significance, data quality and relevance,
and proposal feasibility. Collaborative proposals from different labs are
encouraged and prioritized. We expect an initial expression of interest via
mail to
[email protected]<mailto:[email protected]> by
15th Oct 2024, followed by a full submission on EasyChair by the final
submission deadline.
Proposal
Challenge bidders should submit a challenge proposal for review. The proposal
should be a maximum of two pages (PDF format) including the following
information:
1.
Challenge name
2.
Coordinators
3.
Keywords (e.g. classification, generation, transcription)
4.
Definition (one sentence, e.g. automatic mixing for 8 tracks with prediction of
audio effect parameters for gain, pan, compressor, and EQ)
5.
Short description (including the research question the challenge is tackling.
Please mention if it is a follow-up of a past challenge organised elsewhere)
6.
Dataset description: development, evaluation (short description, how much data
is already available and prepared, how long would it take to prepare the rest,
mention if you allow external data/transfer learning or not)
7.
Evaluation method/metric
8.
Baseline system (2 sentences, planned method if you do not have one from the
previous challenge)
9.
Contact person (for main communication, website)
Important dates:
Expression of Interest: 5th November 2024
Final Submission Deadline: 15th Nov. 2024
Conditional Acceptance Notification: 29th Nov 2024
If required, we may ask for additional information regarding the organisation
and scope of the challenge, and ask for a resubmission of the proposal. The
discussion period will span from 2nd Dec 2024 to 17th Jan 2025.
Final Acceptance Notification: 24th Jan 2025
Tentative Timeline
Challenge Descriptions Announced: 31st Jan 2025
Challenges Start: 1st April 2025
Challenges End: 15th June 2025
Challenges Results Announcement: 15th July 2025
We invite challenge organisers to compile a report and present it in the form
of a paper which can be part of the proceedings of the conference.
Paper Submission deadline: 15th August 2025
Enquiries should be sent to:
[email protected]<mailto:[email protected]>
Organising Committee
General Chair: Prof. Joshua Reiss (QMUL)
([email protected]<mailto:[email protected]>)
Papers Co-Chairs: Brecht De Man (PXL-Music) and George Fazekas (QMUL)
([email protected]<mailto:[email protected]>)
Special Sessions Co-Chairs: Soumya Vanka (QMUL) and Franco Caspe (QMUL)
([email protected]<mailto:[email protected]>)
Sponsorships Co-Chairs: Farida Yusuf (QMUL) and Gary Bromham (QMUL)
Conference Website:
https://aes2.org/events-calendar/2025-aes-international-conference-on-artificial-intelligence-and-machine-learning-for-audio/
