Confidence measures for speech recognition: A survey

Abstract

In speech recognition, confidence measures (CM) are used to evaluate reliability of recognition results. A good confidence measure can largely benefit speech recognition systems in many practical applications. In this survey, I summarize most research works related to confidence measures which have been done during the past 10–12 years. I will present all these approaches as three major categories, namely CM as a combination of predictor features, CM as a posterior probability, and CM as utterance verification. Then, I also introduce some recent advances in the area. Moreover, I will discuss capabilities and limitations of the current CM techniques and generally comment on today’s CM approaches. Based on the discussion, I will conclude the paper with some clues for future works.