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Mobile App for Text-to-Image Synthesis

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Mobile Computing, Applications, and Services (MobiCASE 2019)

Abstract

Generating visual representation of textual information is a challenging yet interesting topic with many potential applications. In this paper, we propose a novel approach to visualize natural language sentences using ImageNet to enhance language education. Currently the focus is to assist English language learners in building their vocabulary of common nouns and developing an in-depth understanding of the various prepositions of locations. To achieve this goal, real-world images representing nouns are obtained from ImageNet and their foreground objects of interest are extracted using image segmentation. The objects are then re-arranged on a canvas based on their spatial relationship specified in the sentence. To demonstrate the effectiveness of the proposed approach, we have developed a mobile application that uses the RESTful API to retrieve the images from the web service that operate the image generation program. The prototype mobile application can create visual representations of natural language sentences and a text description of the spatial relationship of objects to assist in learning new vocabulary and spatial prepositions during language education.

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References

  1. Omaggio, A.C.: Pictures and second language comprehension: do they help? Foreign Lang. Ann. 12(2), 107–116 (1979)

    Article  Google Scholar 

  2. Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database. In: IEEE Conference on Computer Vision and Pattern Recognition (2009)

    Google Scholar 

  3. Miller, G.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)

    Article  Google Scholar 

  4. Delgado, D., Magalhaes, J., Correia, N.: Assisted news reading with automated illustration. In: Proceedings of the International Conference on Multimedia – MM 2010 (2010)

    Google Scholar 

  5. Inaba, S. Kanezaki, A., Harada, T.: Automatic image synthesis from keywords using scene context. Ibn: Proceedings of the ACM International Conference on Multimedia – MM 2014 (2014)

    Google Scholar 

  6. Zitnick, C., Parikh, D., Vanderwende, L.: Learning the visual interpretation of sentences. In: 2013 IEEE International Conference on Computer Vision (2013)

    Google Scholar 

  7. Coyne, B., Sproat, R.: WordsEye. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques – SIGGRAPH 2001 (2001)

    Google Scholar 

  8. Mano, T., Yamane, H. Harada, T.: Scene image synthesis from natural sentences using hierarchical syntactic analysis. In: Proceedings of the 2016 ACM on Multimedia Conference – MM 2016 (2016)

    Google Scholar 

  9. Bird, S., Loper, E., Klein, E.: Natural Language Processing with Python. O’Reilly Media Inc., Sebastopol (2009)

    MATH  Google Scholar 

  10. Rother, C., Kolmogorov, V., Blake, A.: GrabCut. ACM Trans. Graph. 23(3), 309 (2004)

    Article  Google Scholar 

  11. Efros, A.: Image Compositing and Blending, Carnegie Mellon University (2007). http://graphics.cs.cmu.edu/courses/15-463/2007_fall/Lectures/blending.pdf. Accessed 4 Feb 2019

  12. Apple Developer Documentation Web Page. https://developer.apple.com/documentation/speech. Accessed 4 Feb 2019

  13. Apple Developer Documentation Web Page. https://developer.apple.com/documentation/foundation/urlsession. Accessed 4 Feb 2019

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Correspondence to Min Chen .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Kang, R., Sunil, A., Chen, M. (2019). Mobile App for Text-to-Image Synthesis. In: Yin, Y., Li, Y., Gao, H., Zhang, J. (eds) Mobile Computing, Applications, and Services. MobiCASE 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 290. Springer, Cham. https://doi.org/10.1007/978-3-030-28468-8_3

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  • DOI: https://doi.org/10.1007/978-3-030-28468-8_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-28467-1

  • Online ISBN: 978-3-030-28468-8

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