Papers

5

Total Citations

41

H-Index

3

About

Hiroki Tanaka is a leading researcher at the intersection of social robotics, human-robot interaction, and multimodal machine learning. His work focuses on creating robots that can understand, assist, and empathize with humans in real-world settings. Tanaka’s most impactful contribution is a novel method for robust understanding of robot-directed speech commands, which uses sequence-to-sequence models with noise injection to overcome the limitations of off-the-shelf automatic speech recognition (ASR) systems. This work, published in 2020, has garnered 19 citations and is foundational for enabling service robots to operate reliably in noisy environments. He has also made significant strides in affective computing, modeling trust and empathy for socially interactive robots (15 citations), and in assistive technology, developing a spoken dialogue robot that monitors the daily lives of elderly people. Beyond dialogue, Tanaka has advanced unsupervised learning for robotics with an active exploration method for multimodal object categorization using a hierarchical Dirichlet process. His earlier work includes the design of an RAA-oriented boarding-type walking robot, demonstrating his long-standing commitment to innovative, human-centered robotic platforms.

Research Focus

Key Achievements

3
H-Index
5
Papers
41
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Robust Understanding of Robot-Directed Speech Commands Using Sequence to Sequence With Noise Injection
19 citations · 2020
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Ritsumeikan University, Nara Institute of Science and Technology, Saitama Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago