Title :
LVCSR rescoring with modified loss functions: a decision theoretic perspective
Author :
Goel, Vaibhava ; Byrne, William ; Khudanpur, Sanjeev
Author_Institution :
Center for Language and Speech Process., Johns Hopkins Univ., Baltimore, MD, USA
Abstract :
The problem of speech decoding is considered in a decision theoretic framework and a modified speech decoding procedure to minimize the expected risk under a general loss function is formulated. A specific word error rate loss function is considered and an implementation in an N-best list rescoring procedure is presented. Methods for estimation of the parameters of the resulting decision rules are provided for both supervised and unsupervised training. Preliminary experiments on an LVCSR task show small but statistically significant error rate improvements
Keywords :
decision theory; decoding; error statistics; learning (artificial intelligence); parameter estimation; speech coding; speech recognition; unsupervised learning; LVCSR rescoring; N-best list rescoring procedure; decision rules; decision theory; experiments; general loss function; modified loss functions; parameter estimation; speech decoding; speech recognition; supervised training; unsupervised training; word error rate; Acoustics; Bayesian methods; Decoding; Equations; Error analysis; Loss measurement; Optimization methods; Performance loss; Speech recognition; Testing;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.674458