How Phones Use Your Voice History to Fix Your Typing
Apple's patent for a system that improves text autocorrection by using a database of words the user has previously spoken into their device.
Patent Number
US 9075783
Status
Active
Filing Date
July 22, 2013
Grant Date
July 7, 2015
Expiration
~July 2033 (estimated)
Claims
24
Assignee
Apple Inc
Inventors
Oliver P. WAGNER
Citations
5 forward · 729 backward
What it covers
This patent describes a way to make autocorrect smarter by linking it to your voice history. When you speak into your phone, the device records those words in a database. Later, when you are typing a text or email, the autocorrection engine checks that database to see if you are likely to be typing a word you have said before. If you make a typo, the system uses your personal vocabulary to guess the correct word, rather than just relying on a generic dictionary. It performs this correction automatically as you type, often triggered by a space character.
What it doesn't cover
- —Does not cover autocorrection systems that rely solely on static, pre-installed dictionaries.
- —Does not cover voice-to-text transcription where the entire message is dictated rather than typed.
- —Does not cover predictive text systems that only use typing history without incorporating voice input data.
- —Does not cover hardware-specific keyboard designs or physical key mechanisms.
The clever bit
The innovation is the cross-modal link between voice and text; it treats your microphone as a data source for your keyboard's predictive model, essentially teaching the phone how you talk so it can better understand how you write.
Why it matters
This patent addresses the frustration of generic autocorrect failing to recognize names, slang, or specialized vocabulary that a user frequently speaks. By personalizing the dictionary based on actual speech, it makes mobile communication more efficient. It reflects the industry shift toward context-aware computing where devices learn from user behavior to reduce input errors.
Real-world examples
- 1.iOS QuickType keyboard suggestions
- 2.Personalized language models in modern smartphones
- 3.Dictation-assisted text prediction
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