ToD System
Task-oriented dialogue (ToD) systems aim to build conversational agents capable of completing specific tasks through natural language interaction. Current research focuses on improving data efficiency through techniques like data augmentation and knowledge-aware models, addressing challenges posed by limited annotated data, particularly in spoken language and cross-lingual scenarios. Researchers are also exploring novel model architectures, including transformers and recurrent neural networks, and developing methods to mitigate biases stemming from limited user interaction diversity in training data. These advancements are crucial for building more robust and versatile ToD systems with broader applicability in various domains, such as human resources and customer service.