Faculty of Computing
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Publication Embargo Automated Sinhala Voice Assistant to Manage Tasks using Natural Language Processing - ශ්රී Voice(IEEE, 2022-12-26) Senarathne, K.H.I.R.; Nirash, J.M.I.; Herath, H.M.C.P.; Bandara, V.D.; Wijendra, D; Krishara, JVoice assistants are programs on digital devices that listen and respond to verbal commands. In this dynamic world, users can use these voice assistants to manage daily tasks, plan their day, get answers to problems, and for entertainment purpose. Most of existing voice assistant applications functioned using the English language. Since Sinhala is the native language in Sri Lanka, it is not recognized internationally as well as within Sri Lanka for technical applications. As Sri Lankans are more inclined to use the Sinhala language, it is expected to develop this for the benefit of all the Sri Lankans despite their age and to use their native language through a technical application. Furthermore, the lack of English knowledge will lead to the decline of Information technology literacy. This project expects to take the Sinhala language forward to a standard where it is recognized locally and internationally. Thus, building a mobile application that supports Sinhala voice commands will solve the above-mentioned issues. It will facilitate the individuals to do daily activities efficiently and effortlessly within a less time. Machine Learning and Natural Language Processing are the man technologies used in this project. A computer vision-based algorithm from face detection technology is trained. This application is capable of answering questions and following the instructions for daily tasks and also can be used for entertainment. Apart from the mentioned specialty, it also supports and responds to the Sinhala language that will be shown off on a display.Publication Embargo Escort - Natural Language Processing Based University Students Guidance System(IEEE, 2022-12-26) Srinivasan, D; Uthayakumar, A; Thiyagalingam, P; Ravindran, S; De Silva, H; Kasthururarthna, DUniversities play a significant role in students’ lives and aim to provide the best education, knowledge, and experience. However, university students face many difficulties during their university life including language, communication issues, and the inability to get proper guidance for education and career improvement. This paper proposes an approach to overcome these issues. With the help of Natural Language Processing (NLP), in this paper, several solutions are recommended for the mentioned issues. First, a chatbot helps to communicate with the university administration, where students can ask relevant administrative-related questions. A recommendation system is developed to provide solutions for their psychological issues. Another recommendation system is built for career guidance which will help students to identify the future career of their interest, and the provided mentors will be able to guide them. Another recommendation system identifies the performance of students in each module according to their performance level. The system recommends learning materials to improve their level. With these components, ESCORT – A university students’ guidance system, will make students’ life easier and more efficient.Publication Embargo Adding Common Sense to Robots by Completing the Incomplete Natural Language Instructions(IEEE, 2022-07-18) De Silva, G. W. M. H. P.; Rajapaksha, S; Jayawardena, CThis system is developed to identify and complete the human’s instructions or incomplete sentences given by a user as a command. It would facilitate the interaction between the human and mobile service robots. However, when humans give the instruction, there can be incompleteness or else missing the information related to the environment. That is because humans, generally based on common sense, depending on the environment. Then the human brain can complete all those incomplete sentences by using common sense knowledge. This paper itself introduced a model of a service robot who can compete with the given incomplete instructions, display the related sentences or words, and finally move to the related objects in the environment. First, it will consider and identify the objects in the environment and then consider the given natural language instruction by humans. As a first step of the approach, complete the incomplete sentences. Those sentences are coming as natural language instructions. By parsing it into as the frame can identify the related words by using the created model or can call as language model and here used some identify words from the human common sense also, then the service robot will learn about the commonsense knowledge automatically from the parsing sentences as a speaker. Considering all the parsing sentences, it calculates and measures the accuracy of this service robot model. Simply this is a commonsense reasoning model. The result of the provided solution can enable the robot model that works in a ROS environment to identify and automatically perform the tasks.Publication Embargo Speech Master: Natural Language Processing and Deep Learning Approach for Automated Speech Evaluation(IEEE, 2021-12-06) Kooragama, K.G.C.M; Jayashanka, L. R. W. D; Munasinghe, J. A; Jayawardana, K. W; Tissera, M; Jayasingha, T. BEvery English speaker wishes to expertise his/her public speaking skills sharply. However, it is extremely difficult and requires a significant amount of practice and experience on an individual basis. This paper introduces a novel online tool “Speech Master” to practice and improve public English speech delivering skills in a professional manner. Using natural language processing, machine learning, and deep learning approaches, the proposed system analyzes the user's speech in terms of content, grammatical accuracy, grammatical richness, facial expressions, and flow. The accuracy was checked by comparing actual results taken from experts with the predicted results obtained from the tool. “Speech Master” achieves an average accuracy of more than 80% and produces a better overall result. This novel tool benefits English speakers all over the world by meeting the demand for a simple and easy-to-use solution for improving or practicing English speech delivery skills; enhancing oratory skills, boosting confidence, and delivering well-articulated speeches.Publication Embargo Methodology for coping with uncertain information contained in natural language instructions in a robotic system(IEEE, 2020-12-10) Bandara, H. M. Y. L. W; Wijesekera, D. S; Bandara Herath, H. M. T. D; Kodagoda, D. L; Rajapaksha, S, KIntelligent service robots are currently being developed to provide services and assistance in different sectors including domestic and household context. Typically, the service tasks of a domestic service robot involve direct interaction with humans. Humans typically express their ideas through voice communication. However, communication through natural language is imprecise because it tends to contain uncertain and unknown information. Therefore, understanding uncertain terms contained in natural language is a crucial capability that an intelligent service robot should possess. Hence, this project which is named as IntelBot is aimed at developing a methodology to cope with uncertain and unknown words contained in a natural language command given to a domestic service robot. In brief, the proposed system can interpret uncertain commands related to speed such as “go very fast” and the uncertain commands related to time such as “go later”. Additionally, if the robot is instructed to identify an object which is regarded to be unknown, as an example “cup” it can interpret and identify that particular object. And for the entire system, a user-friendly interface is developed for the easy control of the robot and the demonstration of the functionalities.