A Post-Processing System to Yield Reduced Word Error Rates: Recognizer Output Voting Error Reduction [ROVER]
Jonathan G. Fiscus
This paper describes a system developed at NIST to produce a composite Automatic Speech Recognition (ASR) system output when the outputs of multiple ASR systems are available, and for which, in many cases, the composite ASR output has lower error rate than any of the individual systems. The system implements a voting or rescoring process to reconcile differences in ASR system outputs. We refer to this system as the NIST Recognizer Output Voting Error Reduction (ROVER) system. As additional knowledge sources are added to an ASR system (e.g., acoustic and language models), error rates are typically decreased. This paper describes a post-recognition process which models the output generated by multiple ASR systems as independent knowledge sources that can be combined and used to generate an output with reduced error rate. To accomplish this, the outputs of multiple of ASR systems are combined into a single, minimal cost word transition network (WTN) via interactive applications of dynamic programming (DP) alignments. The resulting network is searched by an automatic rescoring or voting process that selects an output sequence with the lowest score.
IEEE Workshop on Speech Recognition and Understanding
dynamic programming (DP), speech recognition
A Post-Processing System to Yield Reduced Word Error Rates: Recognizer Output Voting Error Reduction [ROVER], IEEE Workshop on Speech Recognition and Understanding
(Accessed December 10, 2023)