Deciphering scribbles: Why converting handwriting to text requires advanced AI

“Paperwork” used to be a common word in the office, but in our increasingly digital world, you might have trouble remembering the last time you heard it. Still, many organizations continue to use paper forms throughout their operations to avoid the challenges and support costs of large-scale digitization. However, in avoiding the time and cost of digitization, companies may end up applying more time and manual labor to processing their paper forms, especially when it comes to inputting information from handwritten documents.

Putting pen to paper is especially common for intaking customer information. Organizations in healthcare, finance, retail, and beyond, often use paper forms for

• New patient questionnaires
• Deposit slips
• Retail loyalty card applications
• Membership applications

In most fully digitized offices, processing these documents always creates extra work. Handwritten information is useless until it’s in a format computers can understand. Employees have to scan each page and run it through an OCR (optical character recognition) program or manually type in the data.

Doing this for a few documents here and there isn’t an issue. But when it involves dozens or hundreds of documents per day, it creates serious workflow challenges that eat up a lot of resources. Automation has taken a lot of the pain out of these processes, but many tools still struggle with converting handwriting to text.

Fortunately, advanced AI is starting to ease the burden.

The limits of legacy OCR

When an OCR program scans a document image, it examines each pixel and its relationship to the others around it, looking for specific patterns. On simple text documents, it’s actually the shape of white and dark pixels that create letters, numbers, and other characters. When OCR recognizes a shape that’s a character, it converts it into text a computer can recognize, essentially replicating the process a data entry specialist would follow as they re-type the words from a paper document into a computer.

The earliest forms of OCR could only recognize specific fonts and colors. Over time, their ability to recognize patterns grew, encompassing more fonts, as well as text from images with more colors and design flourishes, such as flyers, marketing pamphlets and other complex documents. Eventually, OCR evolved to recognize handwritten print letters. Of course, the accuracy was incredibly low, requiring almost as much manual processing as data entry.

Why we need advanced AI for converting handwriting to text

Deciphering handwriting takes much more cognitive processing than just recognizing patterns. Reading the handwriting of even just one person requires the ability to recognize an incredible number of character variations and handwriting styles compared to printed text.

Think about your own (unconscious) strategy for reading printed letters and cursive. First, you recognize shapes as letters. If certain characters aren’t legible, you may look at the surrounding letters and words for context to discern what the unreadable characters are. Sometimes, it’s impossible to even read your own handwriting, especially if you scribbled a note in a hurry. 

For a machine to decipher cursive requires algorithmic training on the direction of pen strokes and how different letters flow into each other. Without this kind of base knowledge and analytical ability, OCR will have trouble even seeing cursive as writing.

We are still a long way off from having free-thinking machines, but artificial intelligence has advanced enough to perform some of its own simple versions of our cognitive processes. And until we can teach them to fully replicate our reasoning abilities, we can train algorithms with specific data to improve accuracy.

Fully automating the process of converting handwriting to text is a challenge people have been working on for a long time. Technology is just now providing enough accuracy and speed to support business processes, improving productivity for businesses that haven’t switched to fully digitized forms. Investing in and implementing AI capable of processing handwriting helps companies stay ahead of the curve, and remain competitive in a fast-paced marketplace.