NLP Development of AI- Driven Autonomous Socially Assistive Robots (SAR)
DOI:
https://doi.org/10.6977/IJoSI.202602_10(1).0001Keywords:
socially assistive robot, natural language processing (NLP), Large Language Model (LLM), artificial intelligence, question-answeringAbstract
This study focuses on addressing the growing need for localized language support in Socially Assistive Robots (SARs) due to rising labor costs and the limitations of human labor in developed countries. The research specifically aims to develop a Turkish Natural Language Processing (NLP) module to enhance SARs' social interaction capabilities and integration into smart living spaces. By leveraging advanced machine learning models such as Transformers and BERT, the study fine-tunes these models for the Turkish language. The system was tested within a university setting, achieving notable results, including a 95% accuracy in voice recognition, 82% in model response accuracy, and a 92% speech comprehensibility rating among native Turkish speakers. These outcomes highlight the potential of SARs with localized language support to improve user experiences in various public and educational settings in Turkey. The research also underscores the importance of integrating NLP into SARs to overcome language barriers and enhance their functionality in diverse linguistic environments. Future work is encouraged to refine these systems and explore their applications in other sectors, contributing to the broader field of AI and robotics.
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