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.

• 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

• Papers sessions
• Workshops
• Symposiums
• Identify trends

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