Supporting dictation speech recognition error correction: the impact of external information

Abstract

Although speech recognition technology has made remarkable progress, its wide adoption is still restricted by notable effort made and frustration experienced by users while correcting speech recognition errors. One of the promising ways to improve error correction is by providing user support. Although support mechanisms have been proposed for inline speech recognition error correction, how to develop user support for third-party error correction has been under studied. To address the unique challenges associated with third-party error correction, external information that is obtained outside of an erroneous sentence was employed in this research. Specifically, three types of external information were selected, including word alternative hypotheses, noisy context and accurate context, and their impacts on dictation speech recognition error correction were assessed empirically. As expected, results revealed the importance of context information to improving both the performance and perception of error correction. Additionally, the results also provided insights into possible effects of word error rate and sentence length on error correction. These findings have significant implications to interface design for transcript proofreading systems.