Interpreting and learning voice commands with a Large Language Model for a robot system
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866913454052343808 |
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| author | Stankevich, Stanislau Dudek, Wojciech |
| author_facet | Stankevich, Stanislau Dudek, Wojciech |
| contents | Robots are increasingly common in industry and daily life, such as in nursing homes where they can assist staff. A key challenge is developing intuitive interfaces for easy communication. The use of Large Language Models (LLMs) like GPT-4 has enhanced robot capabilities, allowing for real-time interaction and decision-making. This integration improves robots' adaptability and functionality. This project focuses on merging LLMs with databases to improve decision-making and enable knowledge acquisition for request interpretation problems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_21512 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Interpreting and learning voice commands with a Large Language Model for a robot system Stankevich, Stanislau Dudek, Wojciech Robotics Computation and Language Neural and Evolutionary Computing Robots are increasingly common in industry and daily life, such as in nursing homes where they can assist staff. A key challenge is developing intuitive interfaces for easy communication. The use of Large Language Models (LLMs) like GPT-4 has enhanced robot capabilities, allowing for real-time interaction and decision-making. This integration improves robots' adaptability and functionality. This project focuses on merging LLMs with databases to improve decision-making and enable knowledge acquisition for request interpretation problems. |
| title | Interpreting and learning voice commands with a Large Language Model for a robot system |
| topic | Robotics Computation and Language Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2407.21512 |