Analysis of the errors produced by the 2004 BBN speech recognition system in the DARPA EARS evaluations

This paper aims to quantify the main error types the 2004 BBN speech recognition system made in the broadcast news (BN) and conversational telephone speech (CTS) DARPA EARS evaluations. We show that many of the remaining errors occur in clusters rather than isolated, have specific causes, and differ to some extent between the BN and CTS domains. The correctly recognized words are also clustered and are highly correlated with regions where the system produces a single hypothesized choice per word. A statistical analysis of some well-known error causes (out-of-vocabulary words, word fragments, hesitations, and unlikely language constructs) was performed in order to assess their contribution to the overall word error rate (WER). We conclude with a discussion of the lower bound on the WER introduced by the human annotator disagreement.