Word and phone level acoustic confidence scoring

This paper presents a word level confidence scoring technique based on a combination of multiple features extracted from the output of a phonetic classifier. The goal of this research was to develop a robust confidence measure based strictly on acoustic information. This research focused on methods...

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Bibliographic Details
Main Authors: Kamppari, S.O., Hazen, T.J.
Format: Conference Proceeding
Language:English
Subjects:
Acoustic measurements
Computer science
Data mining
Feature extraction
Hidden Markov models
Jupiter
Laboratories
Natural languages
Robustness
Speech recognition
Online Access:Request full text
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Summary:This paper presents a word level confidence scoring technique based on a combination of multiple features extracted from the output of a phonetic classifier. The goal of this research was to develop a robust confidence measure based strictly on acoustic information. This research focused on methods for augmenting standard log likelihood ratio techniques with additional information to improve the robustness of the acoustic confidence scores for word recognition tasks. The most successful approach utilized a Fisher linear discriminant projection to reduce a set of acoustic features, extracted from phone level classification results, to a single dimension confidence score. The experiments in this paper were implemented within the JUPITER weather information system. The paper presents results indicating that the technique achieved significant improvements over standard log likelihood ratio techniques for confidence scoring.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2000.862103