eScriptorium is a project whose aim is to provide a framework within which to organise and transcribe handwritten documents (especially old ones) so that the results of the transcription are available for scholarly and digital use, including searching. It uses the escript app to deliver this framework.
It will be appreciated that interpreting old handwriting can be a challenge even for the human brain and so escript should be seen more as an aid to the process of transcription. It allows you to isolate characters, interpret those characters, automatically interpret similar characters, and add your own interpretation etc in order to achieve a complete transcription of the document. The process of Training a neural network and the whole basis of the machine learning environment ensures that where the same handwriting is used a higher degree of automatic recognition should be achieved.
Escript relies on machine learning techniques to provide the recognition mechanism. A neural network (NN) model is initially trained in the handwritten or other characters that are to be recognised and then further characters are supplied to the model with the intention of determining what they represent. The success of the transcription therefore relies on the ability of the NN model to correctly interpret the characters that are supplied to it. This ability is affected both by the quality of the initial training and the inherent capability of the model to correctly apply the training parameters to the supplied characters.
Collaboration is sought to help bring this project to a successful conclusion. Some more work is needed in order to achieve a satisfactory results level. At present only the encog machine learning environment is available for use to construct a Neural Network model. We would like to add Tensorflow as a further option.
We believe eScript offers significant productivity improvements and provides better control over transcription tasks. Join us to help make eScript even better.
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