Compositional Nature of Language to Represent Bimodal Visual- Audial Percepts 
Elakya R1, Himanshu Sinha2, Prince Kumar3, Singh Anubhav Gajendra4, Shubham Gupta5
1Elakya R, Department of CSE, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Himanshu Sinha, Department of CSE, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3Shubham Gupta, Department of CSE, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
4Singh Anubhav Gajendra, Department of CSE, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
5Prince Kumar, Department of CSE, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 25 August 2019 | Revised Manuscript received on 01 September 2019 | Manuscript Published on 14 September 2019 | PP: 88-91 | Volume-8 Issue-5S3, July 2019 | Retrieval Number: E10230785S319/19©BEIESP | DOI: 10.35940/ijeat.E1023.0785S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: We describe the perceptual domain which have a composition domain and also which is rarely ever captured in the existed system. This has happened because they started to learn the composition structure directly. Compositional structures can be divided into separate domains. Keeping that in mind, we propose another way to deal with demonstrating bimodal perceptual areas that expressly relates unmistakable projections over every methodology and after that mutually learns a bimodal meager portrayal. Presently this model will empower compositionality crosswise over particular projections and sum up to percept’s traversed by this compositional premise. For instance, our model can be prepared on red triangles and blue squares; yet, certainly will likewise have learned red squares and blue triangles. To test our model, we have procured another bimodal dataset including pictures and spoken articulations of hued shapes (hinders) in the table top setting.
Keywords: Compositionality, Bimodal, Sparsity, Modality.
Scope of the Article: Nature Inspired Computing