13 citations · 15 across the 4 of their papers we have counts for
8 papers · 1 filter
Kanbun-LM: Reading and Translating Classical Chinese in Japanese Methods by Language Models
Hao Wang, Hirofumi Shimizu, Daisuke Kawahara
Recent studies in natural language processing (NLP) have focused on modern languages and achieved state-of-the-art results in many tasks. Meanwhile, little attention has been paid…
Building a Dialogue Corpus Annotated with Expressed and Experienced Emotions
Tatsuya Ide, Daisuke Kawahara
In communication, a human would recognize the emotion of an interlocutor and respond with an appropriate emotion, such as empathy and comfort. Toward developing a dialogue system w…
Multi-Task Learning of Generation and Classification for Emotion-Aware Dialogue Response Generation
Tatsuya Ide, Daisuke Kawahara
For a computer to naturally interact with a human, it needs to be human-like. In this paper, we propose a neural response generation model with multi-task learning of generation an…
Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extraction
Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan +5
Joint entity and relation extraction aims to extract relation triplets from plain text directly. Prior work leverages Sequence-to-Sequence (Seq2Seq) models for triplet sequence gen…
A System for Worldwide COVID-19 Information Aggregation
Akiko Aizawa, Frederic Bergeron, Junjie Chen +26
The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education. Meanwhil…
Emotion helps Sentiment: A Multi-task Model for Sentiment and Emotion Analysis
Abhishek Kumar, Asif Ekbal, Daisuke Kawahra +1
In this paper, we propose a two-layered multi-task attention based neural network that performs sentiment analysis through emotion analysis. The proposed approach is based on Bidir…