How Machine Learning Takes Handwriting Recognition to New Levels

Advances in machine learning are driving handwriting recognition and other applications forward, promising new capabilities such as context and understanding of sentence structure for organizations that want to capture script from tablets and other devices. As computers based on neural networks grow to understand language the written words that they capture become much more than a string of characters.

Gary Baum, vice president of marketing for MyScript, joins All Analytics Radio at 2 pm EDT on Thursday, August 25, to discuss how those advances in machine learning are changing the nature of handwriting recognition and how recognition software and digital ink can provide benefits to customers. For example, today's handwriting recognition enables text search of human scribble, it can suggest wording options, and it can learn from an individual user's style and habits.

In this interview you also will learn more about how machine learning works today and how computers grow to understand words and visual representations, such as flow charts and mathematical formulas, advancing the human-machine interface (HMI). Hint, the machine learning calls for feeding an awful lot of documents into those systems.

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