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Question Generation based Automatic Learning Assistant in TeluguAuthor: Meghana Bommadi Date: 2022-11-17 Report no: IIIT/TH/2022/129 Advisor:Radhika Mamidi AbstractVirtual assistants are trained to understand and process natural language, which in general are used to follow simple commands like making calls, controlling devices, setting alarms, etc. Customer chat supports in multiple applications also use virtual assistants for resolving simple issues or raising tickets. Human assistants come into action when there is a problem with understanding the issue or understanding the language. The aim here is to have the issues resolved quickly and efficiently by AI instead of a human. The virtual assistance in the past decade has improved vastly over the past decade. Widely used assistants like SIRI, Alexa, and Google Assistant were developed in the 2000s and had significant improvement in understanding natural language over time. Multiple virtual assistants have extensive uses in various fields like entertainment, essential tasks, voice search, etc. Virtual assistance in education is equally necessary as today’s world is much more dependent on online schooling. Learning is a crucial task in a student’s life, which needs assistance in many stages. We started by working on generating questions that will help in cross-checking key points from a passage of text. We worked on the grammatical part of the language Telugu which could give us better results than the state-of-art systems. We tried to create rules that capture the grammatical patterns for potential POS(Parts of Speech) tags that carry important information (instead of tags like auxiliaries) and suffixes of words in a Telugu sentence. In this work we present a learning assistant that tests one’s knowledge and gives feedback that helps a person learn at a faster pace. A learning assistant (based on an automated question generation) has extensive uses in education, information websites, self-assessment, FAQs, testing ML agents, research, etc. Multiple researchers and companies have worked on Virtual Assistance, but majorly in English. We built our learning assistant for the Telugu language to help with teaching in the mother tongue, which is the most efficient way of learning. Our system is built primarily based on Question Generation in Telugu. Many experiments have been conducted on Question Generation in English using multiple methods like rule/template based, supervised, semi supervised [39, 81, 31, 26, 1]. We have built the first hybrid machine learning and rule-based solution in Telugu, which proves efficient for short stories and short passages in children’s books. Our work covers the fundamental question forms with question types such as adjective, yes/no, adverb, verb, when, where, whose, quotative, and quantitative (how many/how much). We constructed rules for question generation using Part of Speech (POS) tags and Universal Dependency (UD) tags along with linguistic information of the surrounding relevant context of the word. Our system is primarily built on question generation in Telugu and is also capable of evaluating the user’s answers to the generated questions Full thesis: pdf Centre for Language Technologies Research Centre |
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