Papers
14
Total Citations
277
H-Index
9
About
Roberto Basili is a prominent computational linguist and AI researcher whose work sits at the intersection of natural language processing and human-robot interaction (HRI). His research has fundamentally advanced how robots understand and respond to human speech, developing computational frameworks that bridge linguistic meaning with physical, real-world environments. Among his most influential contributions is the creation of HuRIC (Human Robot Interaction Corpus), a foundational resource for the field that has garnered 44 citations, alongside groundbreaking discriminative and structured learning approaches to spoken language understanding that have collectively shaped modern robotic communication systems. Basili's research addresses a critical challenge: enabling robots to interpret spoken commands not merely as abstract text, but in context of the environments they inhabit. His grounded language interpretation models and semantic frameworks have proven particularly impactful, demonstrating robustness across service robotics and domestic assistant platforms. More recently, his work has expanded into rehabilitation robotics, integrating natural language interaction with physical therapy applications, reflecting a broader vision of socially embedded AI. With over 260 cumulative citations across his key publications, Basili's contributions represent essential reading for researchers working on conversational AI, embodied cognition, and intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1HuRIC: a Human Robot Interaction Corpus44 citations · 2014
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- 3Textual Inference and Meaning Representation in Human Robot Interaction38 citations · 2013
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- 8Using Semantic Models for Robust Natural Language Human Robot Interaction12 citations · 2015
- 9
- 10Robust Spoken Language Understanding for House Service Robots8 citations · 2016