Spoken Dialogue System

Spoken dialogue systems (SDS) aim to create natural and efficient conversational interfaces between humans and machines, focusing on minimizing latency and improving accuracy in understanding and responding to spoken language. Current research emphasizes enhancing robustness through techniques like data augmentation (including methods leveraging LLMs and incorporating multimodal information), improving real-time dialogue breakdown detection using multimodal contextual models, and addressing challenges posed by low-resource languages and noisy speech inputs. These advancements are crucial for developing more effective and inclusive SDS applications across various domains, including healthcare, customer service, and education.