We present TacoBot, a task-oriented dialogue system built for the inaugural Alexa Prize TaskBot Challenge, which assists users in completing multi-step cooking and home improvement tasks. TacoBot is designed with a user-centered principle and aspires to deliver a collaborative and accessible dialogue experience. Towards that end, it is equipped with accurate language understanding, flexible dialogue management, and engaging response generation. Furthermore, TacoBot is backed by a strong search engine and an automated end-to-end test suite. In bootstrapping the development of TacoBot, we explore a series of data augmentation strategies to train advanced neural language processing models and continuously improve the dialogue experience with collected real conversations. At the end of the semifinals, TacoBot achieved an average rating of 3.55/5.0.
翻译：我们介绍塔科博特,这是为成立亚历山大奖任务包挑战而建立的一个面向任务的对话系统,它帮助用户完成多步烹饪和家居改造任务。塔科博特设计了一个以用户为中心的原则,希望提供合作和无障碍的对话经验。为此,它配备了准确的语言理解、灵活的对话管理以及互动响应生成。此外,塔科博特得到了一个强大的搜索引擎和一个自动端对端测试套件的支持。在开展塔科博特开发工作时,我们探索了一系列数据增强战略,以培训先进的神经语言处理模型,并不断改善所收集的真话对话经验。在半决赛结束时,塔科博特的平均评级为3.55.0。
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