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.
翻译：我们提出ShoppalTalk, 这是一种多端对话面对面的购物搜索系统, 旨在处理超出最先进空档充填系统范围的大型复杂图案。 ShopTalk decouples 对话框管理从实现到实现, 从而允许对话理解系统成为域不可知的系统, 而不是与特定购物应用程序挂钩。 对话理解系统包括一个深层次学习的“ 背景语言理解” 模块, 该模块解释用户的语句, 以及一个主要基于规则的“ 对话- 状态跟踪” (DST), 该模块更新了对话框状态, 并设计了用于实现引擎的搜索请求 。 这两个模块的界面由一套最起码的域名“ 意向操作员” 组成, 指导 DST 如何更新对话状态 。 2020年, StopTalk 被安排在谷歌搜索助理上, 用于购物搜索 。
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