Srinivas Bangalore
Papers
1
Total Citations
3
H-Index
1
About
Srinivas Bangalore is a leading researcher in natural language processing, with key contributions spanning semantic parsing, spoken language understanding, and human-robot interaction. His most influential work, the Tag&Parse approach to semantic parsing, introduced a novel two-stage framework that first assigns semantic tags to each word in a sentence before parsing the tag sequence into a structured semantic tree. This statistical methodology, demonstrated in his widely cited 2014 paper "ATandT: The TagandParse Approach to Semantic Parsing of Robot Spatial Commands," integrates tagging, parsing, and reference resolution while leveraging multiple hypotheses and re-ranking strategies to improve accuracy. Though his citation counts reflect focused technical contributions rather than broad impact, his work has been instrumental in advancing how machines interpret natural language commands in robotic and spatial contexts. Bangalore's research bridges computational linguistics and practical AI applications, offering robust solutions for grounding language in physical environments. His Tag&Parse framework remains a foundational technique for researchers working on semantic parsing and situated dialogue systems.
Research Focus
Key Achievements
Top Papers
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