SOLOIST: Building Task Bots at Scale with Transfer Learning and Machine Teaching

Understand

We present a new method SOLOIST that uses transfer learning and machine teaching to build task bots at scale.

• We parameterize classical modular task-oriented dialog systems using a Transformer-based auto-regressive language model, which subsumes different dialog modules into a single neural model.
• We pre-train, on heterogeneous dialog corpora, a task-grounded response generation model, which can generate dialog responses grounded in user goals and real-world knowledge for task completion.
• The pre-trained model can be efficiently adapted to accomplish new tasks with a handful of task-specific dialogs via machine teaching, where training samples are generated by human teachers interacting with the system.