The Interactive Cookbook

互动食谱

• 批准号: 461220770
• 负责人: Professor Dr. Alexander Koller
• 金额: --
• 依托单位: Lehrstuhl für Computerlinguistik (Prof Koller)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/461220770?language=en
• 关键词: Interactive; Cookbook

The goal of this project is to develop an "Interactive Cookbook": a spoken dialogue system that guides users through the process of cooking a dish. The system will analyze individual recipe texts for a given dish offline and aggregate them into a symbolic recipe graph, which captures alternative ways in which the recipe can be explained and carried out. At dialogue time, a natural language understanding (NLU) component will process user requests regarding the dish, and a natural language generation (NLG) component will generate step-by-step instructions in English or German based on the recipe graph. The dialogue system will adapt the level of detail at which it presents the recipe to the user's needs.In developing such an Interactive Cookbook, we will face a number of research challenges. First, cooking recipes are a rather specific type of text, and NLU methods trained on main- stream corpora will have to be adapted to the recipe domain. We will also consolidate different recipes for the same dish into a single representation, so we can switch to different levels of detail as required for the user.Second, we will have to refine neural word embeddings to capture domain-specific meaning distinctions: “salt” and “sugar” are distributionally very similar, but confusing one for the other in a recipe will drastically change the dish.Finally, we will have to move beyond current methods in NLG: grammar-based methods run into coverage problems when explaining arbitrary recipes, and neural methods such as those in recent approaches to abstractive summarization struggle to produce language which conveys a given meaning. One focus of the project will therefore be to generate instructions which are semantically true to the underlying recipes, by conditioning a neural NLG system on symbolic recipe graphs.

这个项目的目标是开发一个“互动食谱”：一个口语对话系统，指导用户烹饪菜肴的过程。该系统将离线分析给定菜肴的各个食谱文本，并将其聚合成一个符号食谱图，该图捕捉了可以解释和执行食谱的替代方式。在对话时，自然语言理解（NLU）组件将处理用户关于菜肴的请求，自然语言生成（NLG）组件将基于食谱图生成英语或德语的分步指令。对话系统将根据用户的需要调整食谱的详细程度。在开发这样一本交互式食谱的过程中，我们将面临许多研究挑战。首先，烹饪食谱是一种相当特定的文本类型，在主流语料库上训练的NLU方法必须适应食谱领域。我们还将把同一道菜的不同菜谱整合到一个单一的表示中，这样我们就可以根据用户的需要切换到不同的细节层次。其次，我们必须细化神经词嵌入，以捕捉特定领域的含义差异：“盐”和“糖”在分布上非常相似，但在食谱中混淆两者会彻底改变这道菜。最后，我们将不得不超越NLG中当前的方法：基于语法的方法在解释任意配方时遇到覆盖问题，而诸如最近抽象摘要方法中的神经方法努力产生传达给定含义的语言。因此，该项目的一个重点是通过在符号配方图上调节神经NLG系统来生成语义上真实的底层配方指令。