Classroom Slide Narration System

TL;DR

This paper introduces a Classroom Slide Narration System (CSNS) that automatically generates audio descriptions for slide content, aiding visually impaired students by accurately segmenting and extracting slide information using a novel architecture and multiple modules.

Contribution

The paper proposes a new segmentation architecture, CSSN, tailored for slide images, and integrates OCR, figure classification, and other modules to improve accessibility for VI students.

Findings

9.54% segmentation accuracy improvement on WiSe dataset

Better user feedback compared to Facebook's AAT and Tesseract

Effective extraction of slide content for narration

Abstract

Slide presentations are an effective and efficient tool used by the teaching community for classroom communication. However, this teaching model can be challenging for blind and visually impaired (VI) students. The VI student required personal human assistance for understand the presented slide. This shortcoming motivates us to design a Classroom Slide Narration System (CSNS) that generates audio descriptions corresponding to the slide content. This problem poses as an image-to-markup language generation task. The initial step is to extract logical regions such as title, text, equation, figure, and table from the slide image. In the classroom slide images, the logical regions are distributed based on the location of the image. To utilize the location of the logical regions for slide image segmentation, we propose the architecture, Classroom Slide Segmentation Network (CSSN). The unique attributes of this architecture differs from most other semantic segmentation networks. Publicly available benchmark datasets such as WiSe and SPaSe are used to validate the performance of our segmentation architecture. We obtained 9.54 segmentation accuracy improvement in WiSe dataset. We extract content (information) from the slide using four well-established modules such as optical character recognition (OCR), figure classification, equation description, and table structure recognizer. With this information, we build a Classroom Slide Narration System (CSNS) to help VI students understand the slide content. The users have given better feedback on the quality output of the proposed CSNS in comparison to existing systems like Facebooks Automatic Alt-Text (AAT) and Tesseract.