Are some speech recognition errors easier to detect than others?

Authors:
Yongmei Shi;Lina Zhou
Affiliations:
University of Maryland, Baltimore, MD;University of Maryland, Baltimore, MD
Venue:
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
Year:
2007

Citing 2
Cited 1

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Computational Linguistics
Discovering Cues to Error Detection in Speech Recognition Output: A User-Centered Approach

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Third-party error detection support mechanisms for dictation speech recognition

Interacting with Computers

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Abstract

This study investigates whether some speech recognition (SR) errors are easier to detect and what patterns can be identified from those errors. Specifically, SR errors were examined from both non-linguistic and linguistic perspectives. The analyses of non-linguistic properties revealed that high error ratios and consecutive errors lowered the ease of error detection. The analyses of linguistic properties showed that ease of error detection was associated with changing parts-of-speech of reference words in SR errors. Additionally, syntactic relations themselves and the change of syntactic relations had impact on the ease of error detection.