论文标题
Wikihow的意图检测
Intent Detection with WikiHow
论文作者
论文摘要
现代面向任务的对话框系统需要可靠地了解用户的意图。在移动新域或新语言时，意图检测最具挑战性，因为很少有带注释的数据。为了应对这一挑战，我们提出了一系列经过预定的意图检测模型。我们的模型能够预测许多动作的广泛预期目标，因为它们在全面的教学网站Wikihow上进行了培训。我们的模型在SNIPS数据集，模式引导的对话数据集以及Facebook多语言对话框数据集的所有3种语言上实现了最新的结果。我们的模型还表现出强劲的零和少量性能，在所有数据集中仅使用100个培训示例达到75％以上的精度。
Modern task-oriented dialog systems need to reliably understand users' intents. Intent detection is most challenging when moving to new domains or new languages, since there is little annotated data. To address this challenge, we present a suite of pretrained intent detection models. Our models are able to predict a broad range of intended goals from many actions because they are trained on wikiHow, a comprehensive instructional website. Our models achieve state-of-the-art results on the Snips dataset, the Schema-Guided Dialogue dataset, and all 3 languages of the Facebook multilingual dialog datasets. Our models also demonstrate strong zero- and few-shot performance, reaching over 75% accuracy using only 100 training examples in all datasets.
