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diagram-accessibility.html
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<!DOCTYPE html>
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<div class="project-module module-4"></div><h2 style="float:left; font-size:40px; color:#fff; padding:17px; font-weight:bold;">Diagram Accessibility</h2>
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<p style="color:#fff;">The understanding of diagram is crucial for understanding STEM content. It reduces the amount of effort required to understand the critical concepts and provide better visualization. Sometime, even the textual description in the book is highly ambiguous without access to the diagram. Similarly, for graphs, its hard to get visualization from tabular data. Diagram based questions also enhance the reasoning ability of the student. Visually Impaired students are generally deprived of the access of the diagrams. This requires Alt-text generation/augmentation, which becomes more challenging when it comes to handling verbosity on the basis of context. Image description APIs are currently far behind in providing the adequate description of textbook diagrams. Tools and techniques are required for automatic alt-text generation/augmentation.
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<h2>Text/Caption Augmentation for Experimental Setup Diagrams</h2>
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About: In this project, we are working on a template based approach for augmenting textual description / caption provided in the textbook for experimental setup diagram, which is ono of the profound category of diagrams found in STEM textbooks. This approach requires image processing to detect objects and their positionings, which can help in understanding the interaction among the objects. Further, Natural language processing techniques will be used to generate the precise description of the diagram.
<br><br>Students: Akshansh Chahal (BTP 2017)</p>
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<h2>Description of Geometrical Diagrams</h2>
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About: In this project, we are working on generating textual description for the geometry diagrams, which is one of the most commonly found diagram in mathematics textbooks. The objective involves to come up with a precise description which can lead to exact replication of the diagram. Further analysis will be done to make the description contextual dependent and least verbose. Image processing techniques are used for finding primitive shapes along with its properties and associated labels. Then the natural language processing techniques will be explored to generate the desired textual description.
<br><br>Students: Jyoti, Sruti Goyal, Tuhina Verma (MiniP 2018)</p>
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