Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

A Post-Processing System to Yield Reduced Word Error Rates: Recognizer Output Voting Error Reduction [ROVER]

Published

Author(s)

Jonathan G. Fiscus

Abstract

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.
Citation
IEEE Workshop on Speech Recognition and Understanding

Keywords

dynamic programming (DP), speech recognition

Citation

Fiscus, J. (1997), A Post-Processing System to Yield Reduced Word Error Rates: Recognizer Output Voting Error Reduction [ROVER], IEEE Workshop on Speech Recognition and Understanding (Accessed May 24, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created December 17, 1997, Updated February 17, 2017