A decision-theoretic framework for the evaluation of language models used in speech recognizers

Authors:
J. R. Deller, JR.;K. H. Desai;Y. P. Yang
Affiliations:
Department of Electrical & Computer Engineering, Michigan State University, 2120 EB, East Lansing, MI 48824-1226, USA e-mail: deller@egr.msu.edu, desai@egr.msu.edu;Department of Electrical & Computer Engineering, Michigan State University, 2120 EB, East Lansing, MI 48824-1226, USA e-mail: deller@egr.msu.edu, desai@egr.msu.edu;Department of Electrical & Computer Engineering, Michigan State University, 2120 EB, East Lansing, MI 48824-1226, USA e-mail: deller@egr.msu.edu, desai@egr.msu.edu
Venue:
Natural Language Engineering
Year:
2005

Citing 5
Cited 0

Fundamentals of speech recognition

Fundamentals of speech recognition
An introduction to signal detection and estimation (2nd ed.)

An introduction to signal detection and estimation (2nd ed.)
Discrete Time Processing of Speech Signals

Discrete Time Processing of Speech Signals
Acoustical and Environmental Robustness in Automatic Speech Recognition

Acoustical and Environmental Robustness in Automatic Speech Recognition
Semantic Clustering for Adaptive Language Modeling

ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

An analytical method for design and performance analysis of language models (LM) is described, and an example interactive software tool based on the technique is demonstrated. The LM performance analysis does not require on-line simulation or experimentation with the recognition system in which the LM is to employed. By exploiting parallels with signal detection theory, a profile of the LM as a function of the design parameters is given in a set of curves analogous to a receiver-operating-characteristic display.