Papers by Yushi Aono
Generating Responses that Reflect Meta Information in User-Generated Question Answer Pairs (2020.lrec-1)
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Takashi Kodama, Ryuichiro Higashinaka, Koh Mitsuda, Ryo Masumura, Yushi Aono, Ryuta Nakamura, Noritake Adachi, Hidetoshi Kawabata
| Challenge: | Existing approaches to realize consistent personalities require expensive data collection. |
| Approach: | They propose to collect question-answer pairs for particular characters from online users . meta information such as emotion and intimacy was also collected . |
| Outcome: | The proposed method can be used to train neural conversational models with high quality questions and meta information. |
Multi-task and Multi-lingual Joint Learning of Neural Lexical Utterance Classification based on Partially-shared Modeling (C18-1)
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| Challenge: | Existing studies on multitask and multilingual joint learning focus on cross-task or cross-lingual knowledge transfer. |
| Approach: | They propose to divide state-of-the-art neural lexical utterance classification into language-specific components that can be shared between different tasks and different languages. |
| Outcome: | The proposed method is able to support multi-task and multi-lingual learning using Japanese and English data sets with three different lexical utterance classification tasks. |
Adversarial Training for Multi-task and Multi-lingual Joint Modeling of Utterance Intent Classification (D18-1)
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| Challenge: | In multi-task and multi-lingual joint modeling, common knowledge can be efficiently utilized among multiple tasks or multiple languages. |
| Approach: | They propose to introduce language-specific adversarial networks and task-specific language adversarials to purge the task or language dependencies of shared networks. |
| Outcome: | The proposed method is demonstrated using Japanese and English data sets for three different utterance intent classification tasks. |