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Intelligently Aiding Human-Guided Correction of Speech Recognition

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Correcting recognition errors is often necessary in a speech interface. These errors not only reduce users’ overall entry rate, but can also lead to frustration. While making fewer recognition errors is undoubtedly helpful, facilities for supporting user-guided correction are also critical.

We explore how to better support user corrections using Parakeet – a continuous speech recognition system for mobile touch-screen devices. Parakeet’s interface is designed for easy error correction on a handheld device. Users correct errors by selecting alternative words from a word confusion network and by typing on a predictive software keyboard. Our interface design was guided by computational experiments and used a variety of information sources to aid the correction process. In user studies, participants were able to write text effectively despite sometimes high initial recognition error rates. Using Parakeet as an example, we discuss principles we think are important for building effective speech correction interfaces.

This will be a short 15-minute talk.

A copy of the paper as well as a video are available here

This talk is part of the Inference Group series.

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