ABSTRACT
Historically, there are many examples of text with format changes to draw attention to particular syllables, words, or phrases, such as advertisements, instruction manuals, keyword in context in text search, and TALLman lettering to disambiguate similar drug names. These textual enhancements within running text can be automated with natural language processing. For example, NLP can be used to find and rank more important parts of the text such as uncommon words or key sentences. These words can then be formatted to facilitate skimming, such as applying variable weights to make the more important text stand out and less relevant text recede. Automated summarization can be superimposed over detailed text to facilitate orientation and navigation. At the level of individual letters and syllables, the same approach can be used to format text to indicate pronunciation, spelling errors, and abbreviations; or indicate prosody such as pitch and duration.
