Seiichi Yamamoto
Doshisha University, Nagoya University, Osaka University of Economics
Papers
10
Total Citations
81
H-Index
6
About
Seiichi Yamamoto is a pioneering researcher at the intersection of robotics, second-language acquisition, and human-computer interaction. His primary research areas include robot-assisted language learning (RALL), multimodal communication, and conversational artificial intelligence. Yamamoto’s most significant contribution is the development of the “joining-in-type” RALL system, which employs two humanoid robots—one acting as a teacher and the other as a peer—to create immersive, realistic conversational environments for language learners. This innovative approach leverages implicit learning, where grammatical patterns and vocabulary are acquired naturally through interaction rather than explicit instruction. His work has demonstrated measurable learning effects, with studies showing retention of grammatical structures and increased learner motivation. Yamamoto’s research has accumulated over 80 citations, with his most-cited paper (2017) receiving 20 citations. He has also contributed to multimodal corpus development for modeling turn management in multi-party conversations and created WikiTalk, a bilingual robot capable of fluent conversation using English and Japanese Wikipedia content. Notably, his recent work extends into soft robotics with self-healing polymers, showcasing his versatility. Yamamoto’s systems represent a significant step toward more natural, engaging, and effective technology-mediated language education.
Research Focus
Key Achievements
Top Papers
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- 3Joining-in-type Humanoid Robot Assisted Language Learning System10 citations · 2016
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- 5Multimodal Corpus of Multi-party Conversations in Second Language7 citations · 2012
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