论文标题
自我注意模型的构建和评估，用于语义理解句子最终粒子
Construction and Evaluation of a Self-Attention Model for Semantic Understanding of Sentence-Final Particles
论文作者
论文摘要
句子 - 最终粒子在日语口语中起着至关重要的作用，因为它们表达了说话者对命题和/或对话者的精神态度。它们是在早期获得的，并且在日常对话中经常发生。但是，对于获取句子最终粒子的计算模型几乎没有提议。本文提出了主观BERT，这是一种自我发挥的模型，除了语言和图像作为输入外，还具有各种主观感官，并了解单词和主观感官之间的关系。一项评估实验表明，该模型了解“ Yo”的用法，该模型表达了发言人传达新信息的意图，以及“ NE”的意图，该信息表示说话者确认某些信息共享的愿望。
Sentence-final particles serve an essential role in spoken Japanese because they express the speaker's mental attitudes toward a proposition and/or an interlocutor. They are acquired at early ages and occur very frequently in everyday conversation. However, there has been little proposal for a computational model of acquiring sentence-final particles. This paper proposes Subjective BERT, a self-attention model that takes various subjective senses in addition to language and images as input and learns the relationship between words and subjective senses. An evaluation experiment revealed that the model understands the usage of "yo", which expresses the speaker's intention to communicate new information, and that of "ne", which denotes the speaker's desire to confirm that some information is shared.
