Implementing a Natural Language Conversational Interface for Indian Language Computing

Jindal, Rahul M.; Kumar, Rohit; Sahajpal, Ritvik; Sofat, Sanjeev; Singh, Shailendra

doi:10.1080/02564602.2004.11417152

Cited by 4 publications

(2 citation statements)

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“…The model [54] can make a particular person dataset from the Qur'an for preparing this chatbot, in light of. One endeavor is Deepti [55], an intelligent web-based visit program that can talk in Hindi. Deepti types and answers in romanized Hindi.…”

Section: Adaptability With Regional Languagesmentioning

confidence: 99%

Machine learning implementation using bots

Patel

2022

Preprint

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For advanced human-computer interaction, research on natural language processing is on trend, resulting in the development of innate and natural interaction modalities, such as chatbots. A chatbot is a software application that makes it possible to conduct conversations in a natural language for various user queries in an online mode, thus grabbing much attention in business and commercial applications. Various chatbot models have been reported previously, but no comprehensive chatbot model has been available for processing all human languages under all user applications. As a result, researchers have started to dedicate their efforts to develop their own chatbot model based on a specific language for some specific applications. With this specific goal, we have proposed a chatbot model for conservation in the English language that handles queries in the sociological domain based on a hybrid approach. The proposed chatbot model using generative and retrieval techniques, can handle one-word as well as descriptive responses to user sociological queries. We claim that the proposed chatbot can meet the needs of small-to medium-sized organizations for their research queries, and that this model is comparatively more interactive, easy to maintain, and cost-effective against the previous models.

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Section: Adaptability With Regional Languagesmentioning

confidence: 99%

Machine learning implementation using bots

Patel

2022

Preprint

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“…It reads the TEMPLATE and takes an appropriate action. e processing of dialog response which is being produced by a TEMPLATE diverges from being as simple as replicating the contents to the response [25].…”

Section: Response Generatormentioning

confidence: 99%

Framework for Educational Domain-Based Multichatbot Communication System

Memon

Aghian

Sarfraz

et al. 2021

Scientific Programming

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Education is an area where innovation moves slowly. In this study, we will propose a framework with a novel approach that will support the development of a multi-interactive chatbot’s system for an educational area using AIML 2.0. The system will facilitate the students for their learning towards an outcome-based education domain. The proposed framework will be composed of a user module which consists of user and user interface, chat agents module which will respond to the user query, chatbot KB which will act as the brain for the chatbot system, and socket system for establishing the communication link. Finally, the proposed system will be evaluated using a confusion matrix. The multichatbot communication system will support text-based dialogues on a limited set of questions related to education. However, the system will be implemented in java. The outcomes of this research will be useful for the education sector where these intelligent systems will help the students in schools, universities, and other training scenarios.

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