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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5600
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dc.contributor.authorMittal A.-
dc.contributor.authorKumar P.-
dc.contributor.authorPratim Roy, Partha-
dc.contributor.authorBalasubramanian R.-
dc.contributor.authorChaudhuri B.B.-
dc.date.accessioned2020-10-06T15:56:51Z-
dc.date.available2020-10-06T15:56:51Z-
dc.date.issued2019-
dc.identifier.citationIEEE Sensors Journal (2019), 19(16): 7056-7063-
dc.identifier.issn1530437X-
dc.identifier.urihttps://doi.org/10.1109/JSEN.2019.2909837-
dc.identifier.urihttp://repository.iitr.ac.in/handle/123456789/5600-
dc.description.abstractSign language facilitates communication between hearing impaired peoples and the rest of the society. A number of sign language recognition (SLR) systems have been developed by researchers, but they are limited to isolated sign gestures only. In this paper, we propose a modified long short-term memory (LSTM) model for continuous sequences of gestures or continuous SLR that recognizes a sequence of connected gestures. It is based on splitting of continuous signs into sub-units and modeling them with neural networks. Thus, the consideration of a different combination of sub-units is not required during training. The proposed system has been tested with 942 signed sentences of Indian Sign Language (ISL). These sign sentences are recognized using 35 different sign words. The average accuracy of 72.3% and 89.5% has been recorded on signed sentences and isolated sign words, respectively. © 2001-2012 IEEE.-
dc.language.isoen_US-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.relation.ispartofIEEE Sensors Journal-
dc.subjectdeep neural networks-
dc.subjectdepth sensors-
dc.subjectleap motion sensor-
dc.subjectSign language recognition-
dc.titleA Modified LSTM Model for Continuous Sign Language Recognition Using Leap Motion-
dc.typeArticle-
dc.scopusid56763507700-
dc.scopusid57212043589-
dc.scopusid56880478500-
dc.scopusid7103127999-
dc.scopusid57210120100-
dc.affiliationMittal, A., Department of Computer Science Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India-
dc.affiliationKumar, P., Department of Computer Science Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India-
dc.affiliationRoy, P.P., Department of Computer Science Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India-
dc.affiliationBalasubramanian, R., Department of Computer Science Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India-
dc.affiliationChaudhuri, B.B., Techno India University, Kolkata, 700091, India-
dc.description.correspondingauthorKumar, P.; Department of Computer Science Engineering, Indian Institute of Technology RoorkeeIndia; email: pradeep.iitr7@gmail.com-
Appears in Collections:Journal Publications [CS]

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