Audio-Centric AI: Towards Real-World Multimodal Reasoning and Application Use Cases

This Audio-aaai workshop focuses on recent and emerging directions in the field of audio understanding, particularly beyond conventional tasks such as sound event detection (SED) and acoustic scene classification (ASC). There is growing interest in intelligent systems that can understand and act on rich auditory scenes in realistic environments. With the increasing prevalence of audio-capable edge devices, smart assistants, and wearable sensors, understanding audio in a robust, multimodal, and privacy-conscious manner is more crucial than ever. While major conferences like AAAI, NeurIPS, and ICASSP have explored isolated components of this area, this workshop aims to provide a comprehensive platform that brings together researchers from AI, audio signal processing, and machine learning communities. Related workshops in the past include: DCASE Challenges and Workshops focuses on sound event and scene recognition; WASPAA and EUSIPCO workshops focus on audio processing; and 2023 NeurIPS Workshop on Machine Learning for Audio focused on generation models.

This workshop builds on prior community-building efforts to create a focused venue for advancing audio intelligence in real-world applications. It aims to tackle key technical challenges including multimodal contextualization, the development of robust evaluation benchmarks, and strategies for successful industry deployment. Such a dialogue is especially timely given the rapid advancements in AI and the growing demand for intelligent, context-aware systems across diverse domains ranging from robotics to healthcare.