Joint Audio

Joint audio research focuses on developing models that process and understand multiple audio streams or integrate audio with other modalities like video or text, aiming for improved performance in tasks such as speech recognition, music generation, and audio-visual scene understanding. Current research heavily utilizes diffusion models and transformers, often leveraging pre-trained single-modal models and incorporating techniques like multi-task learning, joint training, and modality-specific adapters to achieve efficient and effective multimodal processing. This field is significant because it advances our ability to create more realistic and nuanced AI systems capable of interacting with complex real-world audio environments, impacting applications ranging from assistive technologies to entertainment and multimedia content creation.