Automatic Text Visualization (ATV) or Text to Scene (TTS) conversation is relatively a new research area covering the domain of Artificial Intelligence, Natural Language Processing, Cognitive computing, Knowledge engineering, Computer Graphics and Psycho-linguistic. ATV is the process of language understanding of an input language text and its utilization as a 3D scene/ virtual environment. ATV has usage in real time applications like language learning for the persons with specific learning disabilities, knowledge transformation (globalization), text summarization, encrypting information for security and Games & entertainment. There are few works reported in English and other European languages but none for Indian Language.

We are going to talk about an end-to-end case study for Language Hindi, which is a Morphological rich free word order (MoR-FWO) language with many challenges in its computational processing. The modular architecture is worked upon with pluggable components that is extendible to scope. It consists of three major processing steps: language processing, knowledge base creation and scene generation. We have designed subjective evaluation for the work in absence of standards automatic methodologies on evaluations of ATV systems. Our strategic plan of evaluation carried out to cover Intelligibility, Fidelity and Complexity features of the system. For moderate complex inputs for human to visualize i.e. 1.77/5 the scores are achieved as 3.01/5 i.e. ‘Very Accurate’ and 2.84 /5 ‘Fairly Intelligent’.