Faculty of Computing

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Author: search.filters.author.Harshanath, S. M. BSubject: search.filters.subject.Artificial Intelligence

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    GLIB: Ameliorated English Skills Development with Artificial Intelligence
    (IEEE, 2020-10) Srikanthan, P; Nizar, R; Ravikumar, A; Lalitharan, K; Harshanath, S. M. B; Alosius, J
    In language learning, most of the learners can learn the theory and memorize the sound of a language. However, the ability to speak and learn a language properly requires good practice, experience and good learning strategies. This research is an approach to innovate and improve the language learning strategies along with practices that help to improve the language skills for non-native learners and children who are in the early stage of learning. In this research, the English language will be used to experiment with our solution as the source due to its demand and familiarity in the world. This research is focused on four main skills such as conversation skills, pronunciation skills, listening skills and grammatical skills. This research is done by analyzing the difficulties in each of the skills mentioned above and also discusses and provides details about the solution implemented to improve learning English in an efficient way. The implementation of this research is done by using technologies like natural language processing, machine learning, and deep learning approaches to come up with components to train the learner. The application of this research is delivered by using a cross-platform application called GLIB. The name GLIB is inspired by a library in C language which represents fluency. This mobile application provides facilities to improve all the English language skills mentioned above along with guides, tips, practices, and feedback based on an evaluation to improve the English language.
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    EasyTalk: A Translator for Sri Lankan Sign Language using Machine Learning and Artificial Intelligence
    (IEEE, 2020-12-10) Manoj Kumar, D; Bavanraj, k; Thavananthan, S; Bastiansz, G. M. A. S; Harshanath, S. M. B; Alosious, J
    Sign language is used by the hearing-impaired and inarticulate community to communicate with each other. But not all Sri Lankans are aware of the sign language or verbal languages and a translation is required. The Sri Lankan Sign Language is tightly bound to the hearing-impaired and inarticulate. The paper presents EasyTalk, a sign language translator which can translate Sri Lankan Sign Language into text and audio formats as well as translate verbal language into Sri Lankan Sign Language which would benefit them to express their ideas. This is handled in four separate components. The first component, Hand Gesture Detector captures hand signs using pre-trained models. Image Classifier component classifies and translates the detected hand signs. The Text and Voice Generator component produces a text or an audio formatted output for identified hand signs. Finally, Text to Sign Converter works on converting an entered English text back into the sign language based animated images. By using these techniques, EasyTalk can detect, translate and produce relevant outputs with superior accuracy. This can result in effective and efficient communication between the community with differently-abled people and the community with normal people.