Navigating Multi-turn Conversations: Non-Autoregressive Query Rewriting Architecture for Voice Assistants

Voice Assistants and the Challenge of Navigating Multi-Turn Conversations

Handling multi-turn conversations is a difficult task for voice assistants. They need to understand different types of conversational scenarios, such as steering conversations, carrying over intents, managing disfluencies, retaining relevant entities, and fixing errors. This complexity is compounded by the fact that these scenarios often occur simultaneously in natural language.

A Non-Autoregressive Query Rewriting Architecture

Our solution to this problem is a non-autoregressive query rewriting architecture. This architecture not only addresses the five aforementioned tasks, but also handles complex combinations of these scenarios. Despite being smaller and faster than a fine-tuned T5 model, our proposed model performs just as well or even better on single tasks and outperforms the T5 model in handling combined use-cases.

Source link

Stay in the Loop

Get the daily email from AI Headliner that makes reading the news actually enjoyable. Join our mailing list to stay in the loop to stay informed, for free.

Latest stories

You might also like...