Neural network modeling

HL content: Modeling & Simulation^[1]

Introduction[edit]

Examples include:

Speech recognition[edit]

Speech recognition is the inter-disciplinary sub-field of computational linguistics that develops methodologies and technologies that enables the recognition and translation of spoken language into text by computers.^[2]

Optical character recognition[edit]

Optical character recognition...is the mechanical or electronic conversion of images of typed, handwritten or printed text into machine-encoded text.^[3].

Please note: none of the resources I could find are excellent. But taken together as a whole, they should help improve your understanding of how neural networks work with OCR.

This file is a pdf of a presentation on neural networks and OCR

Natural language processing[edit]

Natural language processing (NLP) is a subfield of computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.^[4]

Standards[edit]

Compare applications that use neural network modelling.

References[edit]

[1] ttp://www.flaticon.com/

[2] ttps://en.wikipedia.org/wiki/Speech_recognition

[3] ttps://en.wikipedia.org/wiki/Optical_character_recognition

[4] ttps://en.wikipedia.org/wiki/Natural_language_processing

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