Develop A Real-Time Closed Captioning Solution with Simplified Captions in Multiple Indian Languages for Accessibility and Inclusivity of Deaf and Hard-Of-Hearing Individuals

1. Whisper: A General-Purpose Speech Recognition Model
Author: Radford, A., et al. (2022)
This paper presents Whisper, which is explained as a model for speech recognition – the translation of speech into text. It supports multiple languages and has real-time captioning capabilities.

2. Indic Trans: Machine Translation Models for Indian Languages
Author: AI4Bharat (2021)
Indic Trans is a translation system developed specifically for Indian languages such as Tamil, Hindi, and Telugu. It is used to generate captions for Indian languages.

3. Google Cloud Speech-to-Text API Documentation
Author: Google Cloud (2023)
This documentation describes Google's speech to text functionality used for real-time and batch transcription of audio data. It also supports many languages and is commonly used for live captioning systems.

4. Transformer-Based Models for Text Simplification
Author: Zhang, X., et al. (2021)
They discuss how the model can be used to simplify complex sentences without changing the meaning of the text. They are useful for making the caption easier to read and understand.

5. Accessibility Technologies for Deaf and Hard-of-Hearing Communities
Author: Smith, J., & Kumar, R. (2020)
However, this paper will discuss various forms of assistive technology that Deaf and hard-of-hearing individuals use, emphasizing the importance of real-time captions.

6. Multilingual Captioning Systems for Real-time Communication
Author: Lee, H., et al. (2022)
This research is concerned with real-time multilingual captioning systems. Such a system confronts several challenges, such as delay or accuracy, in generating live captions.

7. NLP Based Text Simplification Techniques for Captioning
Author: Patel, A., & Verma, S. (2021)
The paper explains various NLP techniques that are used to simplify automatically generated captions. Simplified captions help users in better understanding the spoken content.

8. Deep Neural Networks for End-to-End Speech Recognition
Author: Hinton, G., et al. (2012)
It presented deep neural networks for speech recognition tasks, thereby laying the bedrock for modern speech-to-text systems in use today.

9. Universal Speech Translation with Transformer Models
Author: Jia, Y., et al. (2019)
This paper presents a method to translate speech directly into another language using transformer models. It goes on to justify the basis of multilingual caption generation.

10. Web Content Accessibility Guidelines - WCAG 2.1
Author: World Wide Web Consortium (W3C) (2018)
WCAG 2.1 deals with the accessibility standard for digital content access. That includes standards to do with captioning and the accessibility of multimedia.