Author(s) :   Pranay Parate

Abstract : In recent years, chat bots have become an integral component of digital interaction, providing automated customer service, personal assistance, and information retrieval. This paper explores the design, implementation, and evaluation of a manual chat bots a hybrid system that combines automated responses with manual human intervention. The primary aim is to enhance user experience by leveraging the strengths of both AI-driven automation and human cognitive abilities. The manual chat bots is designed to handle complex queries that require human judgment while maintaining the efficiency of automated systems for routine interactions. We detail the architecture of the chat bots, which includes a robust natural language processing (NLP) engine, a user-friendly interface, and a backend support system for manual intervention. The chat bots design emphasizes flexibility, allowing seamless transitions between automated responses and human assistance. Implementation involved integrating the chat bots within a customer service framework, followed by rigorous testing to ensure reliability and effectiveness. We employed a mixed-methods approach to evaluate the performance of the manual chat bots, using quantitative metrics such as response time, accuracy, and user satisfaction scores, alongside qualitative feedback from users and operators. Results indicate that the manual chat bots significantly improve user satisfaction and efficiency in handling complex queries compared to fully automated systems. The hybrid approach also reduces the cognitive load on human operators by filtering and prioritizing tasks, enabling them to focus on high-value interactions. This paper concludes that manual chat bots represent a promising direction for future research and application in various domains, including customer support, healthcare, and education.

Keywords: Chat bots, Chat bots architecture, Artificial Intelligence, Machine learning, NLU.

DOI : 10.61161/ijarcsms.v12i7.16

Pages : 123-133

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