System and method for automated sign language recognition

Abstract

A method for sign language recognition includes receiving, with an input device, an input based on a plurality of hand movements and postures of a user that correspond to a sequence of signs, extracting a plurality of features from the input corresponding to the plurality of hand movements and postures, identifying, a start of the sequence of signs in the input based on a first set of features inthe plurality of features and a first Hidden Markov Model (HMM) stored in the memory and identifying a first sign in the input based on a second set of features in the plurality of features and a second HMM stored in the memory. The method also includes generating an output corresponding to the first sign from the input.

Description

[0001] priority statement [0002] This application claims priority to U.S. Provisional Application No. 62 / 148,204, entitled "System and Method For Automated Sign Language Recognition," and filed April 16, 2015, the entire contents of which are hereby incorporated by reference This article. This application further claims priority to U.S. Provisional Application No. 62 / 173,878, entitled "SignTransition Modeling and a Scalable Solution to Continuous Sign Language Recognition for Real-World Applications," and filed June 10, 2015, which The entire content of is hereby incorporated herein by reference. technical field [0003] The present disclosure relates generally to the field of sign language recognition (SLR), and more particularly, to systems and methods for SLR including Hidden Markov Models (HMMs), and modeling of non-dominant hand features in sign language recognition. Background technique [0004] Sign language is a natural language primarily used by hard of hearing ...

AI Technical Summary

Problems solved by technology

The second property is that for dominant-hand symbols only, non-dominant-hand signals can be unstable and affected by neighboring symbols or even additional actions

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