4th International Workshop on AI Music Generation and Competition
AIMG 2026 will be held in conjunction with IEEE Big Data 2026 and the Cross-AI Pre-Conference Symposium 2026.
Introduction
Music can touch the hearts of any audience without them possessing any knowledge of its context. The power of music is transcendental, and it stems from the timbre of the instrument(s), the fundamental rhythmic structure and melody, the dynamics, instrumentation, and many more, all of which cooperate in some form of harmony to create the final product. With the recent rise of Artificial Intelligence-Generated Contents (AIGC), AI for music is a promising field full of creativity, novel methodologies, and technologies that are yet to be explored. Currently, AI for music methods have been commonly concentrated on utilizing machine learning and deep learning techniques to generate new music. Despite the significant milestones that have been achieved thus far, many are not necessarily robust for a wide range of applications.
AI music itself is a timely topic. This workshop aims to generate momentum around this topic of growing interest, and to encourage interdisciplinary interaction and collaboration between AI, music, Natural Language Processing (NLP), machine learning, multimedia, Human-Computer Interaction (HCI), audio processing, computational linguistics, and neuroscience. It serves as a forum to bring together active researchers and practitioners from academia and industry to explore emerging advances in AI music generation, including generative models, multimodal music intelligence, music representation and understanding, human-AI co-creation, evaluation, and creative applications in this promising area.
Topics
- Machine learning/AI for music
- Natural language processing for music generation
- Algorithmic music generation
- Music generation based on a specific aspect: lyrical, chordal, motivic, melodic, and rhythmic
- AI-generated lyrics
- AI-generated instrumental audio (including vocal)
- Computational musicology
- AI music interpretation
- AI music data representation
- Music evaluation metrics
- Multiple-channel AI music generation
- AI musical fusion (notes, audio, etc.)
- AI generation for musical performance and expression
- AI music enhancement (e.g. AI-generated instrumentation)
- AI musical ethics
- AI music generation datasets
- Human-Centered Interaction (HCI) for AI music generation
- AI music for neuroscientific applications
- AI-aided music theory applications
- AI bird song generation and translation
- AI natural sound generation
Important Dates
| Date | Milestone |
|---|---|
| October 12, 2026 | Full paper submission (8–10 pages) |
| October 19, 2026 | Short paper submission (5–7 pages) |
| October 26, 2026 | Poster abstract submission (3–4 pages) |
| October 26, 2026 | AI musical composition submission |
| November 2, 2026 | Paper acceptance notification |
| November 2, 2026 | Music acceptance notification |
| November 14, 2026 | Pre-recorded video upload deadline |
| November 14, 2026 | Camera-ready submission deadline |
| November 14, 2026 | Author registration deadline |
| December 14-16, 2026 | Cross-AI Pre-Conference Symposium & IEEE Big Data Workshops |
Submission
All submissions are made through the AirBalloon conference management system portal and evaluated through a unified review process. Upon acceptance, authors may choose to publish in the IEEE Big Data conference proceedings or the indexed Cross-AI conference proceedings, with the corresponding registration fees. Please refer to the respective official registration pages for current fees and registration details. At least one author must register for the corresponding event for the paper/abstract to be published.
1. Papers
Papers follow the IEEE conference manuscript templates (Overleaf or US Letter), in English, as PDF, and are reviewed double-blind.
| Category | Length |
|---|---|
| Full paper | 8–10 pages |
| Short paper | 5–7 pages |
| Poster abstract | 3–4 pages |
2. AI music compositions
The workshop also accepts AI musical compositions.
| Item | Requirement |
|---|---|
| Abstract | 1–2 pages |
| Audio or video | Shareable MP3 or MP4 link, maximum 10 minutes |
| Sheet music | Optional, maximum 8 pages |
Please note that composition submissions not created using AI or algorithmic methods, or including audio exceeding 10 minutes in duration, will not be eligible for participation in the AI Music Composition Competition.
3. Presentation videos
Accepted submissions provide a pre-recorded video.
| Category | Presentation | Q&A |
|---|---|---|
| Full paper | 15 minutes | 3 minutes |
| Short paper | 10 minutes | 2 minutes |
| Poster | 6 minutes | 2 minutes |
Workshop Chairs
- Ellie Zhang, IntelliSky, USA
- Callie Liao, Stanford University, USA
Program Committee
- Zhiqian Chen, Mississippi State University, USA
- Shlomo Dubnov, UC San Diego, USA
- Kaiqun Fu, Texas Christian University, USA
- Jesse Guessford, George Mason University, USA
- Ge Jin, Purdue University, USA
- Fanchun Jin, Google, USA
- Lindi Liao, George Mason University, USA
- Sean Luke, George Mason University, USA
- Jeffrey Morris, Texas A&M University, USA
- Chen Shen, Google, USA
- Alex Wong, Yale University, USA
- Yanjia Zhang, IntelliSky, USA
AIMG Group
This group serves as a forum for notices and announcements of interest to the AI Music Generation (AIMG) community. This includes news, events, calls for papers, calls for collaborations between academia and industry, dataset releases, employment-related announcements, etc.
Welcome to subscribe to the AIMG group.
Previous Workshops
If you are interested in serving on the workshop program committee or paper reviewing, please contact Workshop Chair.