A text-to-picture system for russian language

This paper presents motivation and design of the general purpose text-to-picture synthesis system. The described TTP system is designed for Russian language processing and operates with the natural language analysis subsystem, the stage processing subsystem, and the rendering subsystem. Every processing stage has been described and the basic design ideas of the system architecture have been highlighted. User study has been performed and further work reasons are explained

Text-to-picture tools, systems, and approaches: a survey

Text-to-picture systems attempt to facilitate high-level, user-friendly communication between humans and computers while promoting understanding of natural language. These systems interpret a natural language text and transform it into a visual format as pictures or images that are either static or dynamic. In this paper, we aim to identify current difficulties and the main problems faced by prior systems, and in particular, we seek to investigate the feasibility of automatic visualization of Arabic story text through multimedia. Hence, we analyzed a number of well-known text-to-picture systems, tools, and approaches. We showed their constituent steps, such as knowledge extraction, mapping, and image layout, as well as their performance and limitations. We also compared these systems based on a set of criteria, mainly natural language processing, natural language understanding, and input/output modalities. Our survey showed that currently emerging techniques in natural language processing tools and computer vision have made promising advances in analyzing general text and understanding images and videos. Furthermore, important remarks and findings have been deduced from these prior works, which would help in developing an effective text-to-picture system for learning and educational purposes. - 2019, The Author(s).This work was made possible by NPRP grant #10-0205-170346 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors

Reconstructing Spatial Image from Natural Language Texts

This 1)al>er describes thv und(,rstanding process of the spatial dvs('ril)lions in ,lapam,so. In order to lan(I the described world. the aulhors try to stru('t the geomvtrk' model of the gh)bal scem' from tlw scenic descriptions drawing a space. It is dom hy all experimental COmlmN,r program SPllINT. which takes natural language texts and l)ro(htc('s a modcl of the descrihed wm'ld. To re('onstrm't th(, too(M, the authors extract the q/mlitativ(, spatial constrainits from the text. and represent them as the Iratactical constraints on the spatial attributes of the entities, This make.s it l)ossibh, to expross thv vitgll(qlt,Ss of spatial ('onCel)S and to derive Ihv maxinmlly lfiausi- ble interl)retation froill a clmnk of iilforlllatioll nnilated tm the ('oistraints. The int('rln'vlation rv- th,vts the tomporlu 9' belief ahout the world