Finding consensus in speech recognition: word error minimization and other applications of confusion networks

Details Finding consensus in speech recognition: word error minimization and other applications of confusion networks Finding consensus in speech recognition: word error minimization and other applications of confusion networks

2000-10-07

arxiv.org/abs/cs/0010012v1

Computer Speech and Language 14(4), 373-400, October 2000

Computer Science

Computation and Language

35 pages, 8 figures

Scientific paper

We describe a new framework for distilling information from word lattices to improve the accuracy of speech recognition and obtain a more perspicuous representation of a set of alternative hypotheses. In the standard MAP decoding approach the recognizer outputs the string of words corresponding to the path with the highest posterior probability given the acoustics and a language model. However, even given optimal models, the MAP decoder does not necessarily minimize the commonly used performance metric, word error rate (WER). We describe a method for explicitly minimizing WER by extracting word hypotheses with the highest posterior probabilities from word lattices. We change the standard problem formulation by replacing global search over a large set of sentence hypotheses with local search over a small set of word candidates. In addition to improving the accuracy of the recognizer, our method produces a new representation of the set of candidate hypotheses that specifies the sequence of word-level confusions in a compact lattice format. We study the properties of confusion networks and examine their use for other tasks, such as lattice compression, word spotting, confidence annotation, and reevaluation of recognition hypotheses using higher-level knowledge sources.

Affiliated with

Also associated with

No associations

Rating

Finding consensus in speech recognition: word error minimization and other applications of confusion networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Finding consensus in speech recognition: word error minimization and other applications of confusion networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Finding consensus in speech recognition: word error minimization and other applications of confusion networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-672193