ShopTalk: A System for Conversational Faceted Search

TL;DR

ShopTalk is a conversational search system for shopping that manages complex schemas and separates dialog understanding from fulfillment, enabling domain-agnostic multi-turn interactions.

Contribution

It introduces a decoupled architecture with deep learning-based understanding and rule-based dialog state tracking for complex shopping schemas.

Findings

Deployed on Google Assistant for Shopping in 2020.

Handles large, complex schemas beyond traditional slot-filling systems.

Achieves domain-agnostic dialog management.

Abstract

We present ShopTalk, a multi-turn conversational faceted search system for shopping that is designed to handle large and complex schemas that are beyond the scope of state of the art slot-filling systems. ShopTalk decouples dialog management from fulfillment, thereby allowing the dialog understanding system to be domain-agnostic and not tied to the particular shopping application. The dialog understanding system consists of a deep-learned Contextual Language Understanding module, which interprets user utterances, and a primarily rules-based Dialog-State Tracker (DST), which updates the dialog state and formulates search requests intended for the fulfillment engine. The interface between the two modules consists of a minimal set of domain-agnostic "intent operators," which instruct the DST on how to update the dialog state. ShopTalk was deployed in 2020 on the Google Assistant for Shopping searches.