Estimation of Hidden Neuron Requisite for Predictive Conversion from Sign Language to a Formal Language

Using sign language for communication has existed since millennia and has evolved over the ages to support the hearing impaired to a great extent. There have been numerous wonderful inventions and innovations aimed at improving the living conidtions of the hearing or speech impaired using technology which was contemporary. However, till date there exists no standard that can be shown as a single universal sign language translation system. This is partially due to the research happening in small pockets and lack of technology penetration in some countries. Largely the efforts to design translation are concentrated on Americal Sign Language (ASL) and Thai Sign Language (TSL). Other than the two, Indonasian Sign Language (SIBI) is the front runner in standardising a translation system. In our previous paper we had attempted to develop an ANN based translator for ASL. The system performed as per expectations. However, since the number of hidden neurons was taken as a variable, the estimation still remained a challenge.In this paper, we have developed a system to estimate the number of hidden neurons required for the accurate translation of ASL.