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The Government of India offers various schemes for various classes of citizens. Most of the application forms of schemes to be filled are in English and it is observed that monolingual individuals find it difficult to access and fill the forms. This paper addresses the challenges faced by monolingual individuals in India, particularly the elderly, people with impairments, and those from marginalized communities. The proposed work is to create an interactive system called "Dhvani" voicebot, specifically designed for the Kannada language. It helps users in identifying suitable government schemes and fills forms in English. The proposed system is developed using the RASA chatbot framework and NLP techniques to comprehend user utterances. RNN and SVM algorithms are employed to ensure smooth conversation flow and interaction with the users. To enhance scheme suggestion accuracy, a knowledge graph is created, containing relevant data on government schemes. The intent classification model achieves an accuracy of 97%, indicating its ability to accurately understand user intentions. The integration of a knowledge graph improves the accuracy of scheme identification and suggestion to users. The system automates the process of filling out government scheme forms based on user inputs. Dhvani voicebot system presents a practical solution to address the challenges faced by monolingual individuals in accessing government schemes in India. The high accuracy of intent classification and the use of a knowledge graph contribute to the system's effectiveness. The study suggests that this system can be extended to other languages. An automated tool called "Dhvani" will solve the problem of aged, illiterate and physically challenged persons filling forms in post offices and banks. Most of the schemes, pension funds, cash withdrawal, cash deposit is through these organizations. So. the tool makes the process easier for the above mention persons without the help of others. An intent recognition and interactive tool developed in Kannada Language which is widely spoken in Karnataka, India. The digital resources available in Kannada Language is very sparce. Use of technology like interactive tool, Knowledge graph, RNN and SVM are used in the development of the tool. Government scheme recommendation interactively makes the users to choose the scheme faster in an interactive way. The form is filled automatically and can be edited to rectify mistakes. [ABSTRACT FROM AUTHOR]

The introduction of ChatGPT 3.5 in November 2022 ignited a sensation in the academic community, leaving many astounded by its capabilities. This new release more closely emulates human responses than its predecessors. Among its remarkable capabilities, it can answer questions, catalog items in MARC21, recommend reading lists, and make suggestions on a wide array of topics. To assess ChatGPT’s efficacy in aiding library users, the authors of this paper conducted an experiment comparing ChatGPT’s performance with that of librarians in answering reference questions. Thirty questions were randomly selected from the transaction log of the reference inquiries between June 1, 2023 to July 31, 2023 at the Rider University Libraries. These queries constituted 34% of the total user questions during this two-month period. The authors compared the answers by ChatGPT and those by reference librarians for their accuracy, relevance, and friendliness. The findings indicate that reference librarians markedly outperformed their robotic counterpart. An evident issue arises from ChatGPT’s deficiency in understanding local policies and practices. This consequently hinders its ability to provide satisfactory answers in those areas. OpenAI posits that ChatGPT’s proficiency can be enhanced through targeted fine-tuning using locally specific information. At the moment, ChatGPT remains a great tool for librarians. [ABSTRACT FROM AUTHOR]

This paper explores the effect of chatbot empathy and identity disclosure on willingness to donate (WTD) to a fundraising project and the psychological mechanism in the relationship. In a 3 (information-only vs. cognitive empathy vs. affective empathy) × 2 (chatbot vs. human identity) experiment, 496 US adults had a conversation about a fundraising event with one of six artificial intelligence-powered chatbots. The results revealed that neither chatbot empathy nor identity disclosure has a significant effect on WTD, rejecting the hypotheses. However, the data supported a significant interaction effect between chatbot empathy and identity disclosure on WTD. Moreover, the results suggested that the interaction effect between chatbot empathy and identity disclosure on WTD would be mediated through human likeness and social presence. This study suggests how empathy and human identity of chatbots should be applied with care to avoid the uncanny valley effect. [ABSTRACT FROM AUTHOR]