We introduce TacoBot, a user-centered task-oriented digital assistant designed to guide users through complex real-world tasks with multiple steps. Covering a wide range of cooking and how-to tasks, we aim to deliver a collaborative and engaging dialogue experience. Equipped with language understanding, dialogue management, and response generation components supported by a robust search engine, TacoBot ensures efficient task assistance. To enhance the dialogue experience, we explore a series of data augmentation strategies using LLMs to train advanced neural models continuously. TacoBot builds upon our successful participation in the inaugural Alexa Prize TaskBot Challenge, where our team secured third place among ten competing teams. We offer TacoBot as an open-source framework that serves as a practical example for deploying task-oriented dialogue systems.

TacoBot是一个任务导向的用户中心数字助理，旨在通过多个步骤引导用户完成复杂的现实任务，通过语言理解、对话管理和响应生成组件支持一个协作和有吸引力的对话体验。为了增强对话体验，我们使用LLMs探索了一系列数据增强策略，以持续训练先进的神经模型。TacoBot是我们在首届Alexa Prize TaskBot挑战赛中获得第三名的成功基础上构建的，我们提供TacoBot作为一个开源框架，可作为部署任务导向对话系统的实际示例。

卷起袖子：与协作和引人入胜的以任务为导向的对话系统合作