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Subject: search.filters.subject.Interpreter

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Now showing 1 - 3 of 3
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    PublicationOpen Access
    Implementation of Wyltl: An Imperative Language with a Dual Interpreter – Compiler Architecture
    (SLIIT City UNI, 2025-07-08) Mallawarachchi, D; Jayaweera, Y
    When using a programming language, a common drawback is the prevalence of resource constraints. A lack of resources often results in programs executing faster on high end hardware in comparison to middling or low-end hardware. While a core tenant of programming is optimization, with which entire industries have been built upon, when implementing a programming language, the process becomes significantly more complex. Minute slowdowns in a programming language implementation could very quickly result in major slowdown when executing some code. This paper examines the process of implementing the Wyltl language while balancing the need for performance and resource efficiency provided precious insight and hints towards future optimization, and the unique challenges and opportunities for evolution. Including evaluation of varying parsers, processors and technologies. The evaluation of different parsers and processors was done throughout development with a varied range of programming language optimization techniques being followed as required.
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    PublicationEmbargo
    Sinhala Sign Language Interpreter Optimized for Real – Time Implementation on a Mobile Device
    (2021-08-11) Dhanawansa, V; Rajakaruna, T
    This paper proposes a framework for a vision based Sinhala Sign Language interpreter targeted for implementation on a portable device, optimized for real-time use. The translator is aimed at enabling conversation between a hearing-impaired and a non-signing individual. The scope covers both static and dynamic signs, portrayed using the right hand. Skin segmentation and contour extraction followed by a combination of hand detection and tracking algorithms isolate the signing hand against varied background conditions. A Convolutional Neural Network model was developed to extract and classify the features of the chosen static signs. A standard, expandable dataset of Sinhala static signs was prepared for this task. Dynamic signs were modeled as a tree data structure using a sequence of static signs. The model was optimized using motion based temporal segmentation between consecutive signs, to minimize the processing overhead. The interpreter recorded an average accuracy of 99.5% and 81.2% on the static sign dataset, and combined dataset of static and dynamic signs, respectively. A response time of333 ms was resulted between the occurrence and prediction of a sign, demonstrating the effectiveness of the framework for real-time use.
  • Thumbnail Image
    PublicationEmbargo
    Sinhala Sign Language Interpreter Optimized for Real–Time Implementation on a Mobile Device
    (IEEE, 2021-08-11) Dhanawansa, I. D. V. J; Rajakaruna, R. M. T. P
    This paper proposes a framework for a vision based Sinhala Sign Language interpreter targeted for implementation on a portable device, optimized for real-time use. The translator is aimed at enabling conversation between a hearing-impaired and a non-signing individual. The scope covers both static and dynamic signs, portrayed using the right hand. Skin segmentation and contour extraction followed by a combination of hand detection and tracking algorithms isolate the signing hand against varied background conditions. A Convolutional Neural Network model was developed to extract and classify the features of the chosen static signs. A standard, expandable dataset of Sinhala static signs was prepared for this task. Dynamic signs were modeled as a tree data structure using a sequence of static signs. The model was optimized using motion based temporal segmentation between consecutive signs, to minimize the processing overhead. The interpreter recorded an average accuracy of 99.5% and 81.2% on the static sign dataset, and combined dataset of static and dynamic signs, respectively. A response time of333 ms was resulted between the occurrence and prediction of a sign, demonstrating the effectiveness of the framework for real-time use.