On the benefits of confidence visualization in speech recognition

In a typical speech dictation interface, the recognizer's bestguess is displayed as normal, unannotated text. This ignores potentially useful information about the recognizer's confidence in its recognition hypothesis. Using a confidence measure (which itself may sometimes be inaccurate), we investigated providing visual feedback about low-confidence portions of the recognition using shaded, red underlining. An evaluation showed, compared to a baseline without underlining, underlining lowconfidence areas did not increase user's speed or accuracy in detecting errors. However, we found that when recognition errors were correctly underlined, they were discovered significantly more often than baseline. Conversely, when errors failed to be underlined, they were discovered less often. Our results indicate confidence visualization can be effective ? but only if the confidence measure has high accuracy. Further, since our results show that users tend to trust confidence visuali...

• Type: Conference
• Year: 2008
• Where: CHI
• Authors: Keith Vertanen, Per Ola Kristensson
• Keywords: Accuracy Confidence Measure, CHI 2008, Confidence Visualization, Human Computer Interaction, Keywords Speech Recognition