Multimodal disambiguation of speech recognition

Abstract

The present invention provides a speech recognition system combined with one or more alternate input modalities to ensure efficient and accurate text input. The speech recognition system achieves less than perfect accuracy due to limited processing power, environmental noise, and / or natural variations in speaking style. The alternate input modalities use disambiguation or recognition engines to compensate for reduced keyboards, sloppy input, and / or natural variations in writing style. The ambiguity remaining in the speech recognition process is mostly orthogonal to the ambiguity inherent in the alternate input modality, such that the combination of the two modalities resolves the recognition errors efficiently and accurately. The invention is especially well suited for mobile devices with limited space for keyboards or touch-screen input.

Description

technical field [0001] The present invention relates to a user entering information into a system using an input device. More specifically, the present invention relates to speech recognition combined with a text input clarity system. Background technique [0002] Portable computers have become smaller and smaller over the years. The major size limiting component in the effort to create a smaller portable computer is the keyboard. A portable computer should be at least as large as a standard keyboard, if standard typewriter-sized keys are used. Mini-keyboards have been used in portable computers, but the keys of the mini-keyboards are too small to allow users to operate easily or quickly. Adding a full-size keyboard to a portable computer also prevents the computer from being truly portable. Most portable computers cannot be operated without being placed on a flat work surface that allows the user to type with both hands. A user cannot use a portable computer while movi...

AI Technical Summary

Problems solved by technology

[0017] 1) Handwriting is usually slower than typing;

[0018] 2) On small devices, memory limitations reduce the accuracy of handwriting recognition; and

[0019] 3) Each person's handwriting style is very different from the handwriting style of the person used to train the handwriting software

This has been found to be much more efficient than partial repetition, as the phonetic form has been shown to be incorrect

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