Driving Under the Influence (of Language)
| Autor: | Scott Alan Bronikowski, Daniel Paul Barrett, Jeffrey Mark Siskind, Haonan Yu |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer Networks and Communications
Computer science 02 engineering and technology computer.software_genre Semantics 03 medical and health sciences Annotation 0302 clinical medicine Artificial Intelligence Noun 0202 electrical engineering electronic engineering information engineering Humans Learning Driving Under the Influence Driving under the influence Language business.industry celebrities Robotics Computer Science Applications Comprehension celebrities.reason_for_arrest 020201 artificial intelligence & image processing Artificial intelligence Neural Networks Computer business computer 030217 neurology & neurosurgery Software Natural language Natural language processing |
| Zdroj: | IEEE transactions on neural networks and learning systems. 29(7) |
| ISSN: | 2162-2388 |
| Popis: | We present a unified framework which supports grounding natural-language semantics in robotic driving. This framework supports acquisition (learning grounded meanings of nouns and prepositions from human sentential annotation of robotic driving paths), generation (using such acquired meanings to generate sentential description of new robotic driving paths), and comprehension (using such acquired meanings to support automated driving to accomplish navigational goals specified in natural language). We evaluate the performance of these three tasks by having independent human judges rate the semantic fidelity of the sentences associated with paths. Overall, machine performance is 74.9%, while the performance of human annotators is 83.8%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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