The Schema-Guided Dialogue Dataset
A large-scale multi-domain dataset of over 20k annotated task-oriented dialogues for training and evaluating virtual assistants.
What is The Schema-Guided Dialogue Dataset?
The Schema-Guided Dialogue (SGD) dataset is a large-scale collection of over 20,000 annotated, task-oriented conversations between humans and virtual assistants across 20 domains. It provides structured schemas defining service APIs and rich annotations to support the development and evaluation of dialogue systems for real-world applications like booking, information retrieval, and transactions. The dataset addresses the need for scalable, multi-domain benchmarks that reflect the complexity of actual virtual assistant interactions.
Researchers and engineers working on conversational AI, natural language understanding, and dialogue systems, particularly those focused on task-oriented virtual assistants, dialogue state tracking, and zero-shot generalization.
It offers unparalleled scale and domain diversity with structured schema definitions, enabling robust model training and evaluation. The inclusion of the SGD-X benchmark for linguistic variation robustness and unseen domains for zero-shot testing makes it a comprehensive tool for advancing real-world dialogue system capabilities.
Overview
The Schema-Guided Dialogue Dataset
Use Cases
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