Reconciliation of human and machine speech recognition performance

This paper focuses on resolving a number of issues that appear when the performance of human speech recognition is compared to that of automatic speech recognition. In particular human experimental data suggest that the resulting error is a product of the individual streams. On the other hand, Bayes...

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Bibliographic Details
Published in2009 IEEE International Conference on Acoustics, Speech and Signal Processing pp. 1669 - 1672
Main Authors Pavel, M., Slaney, M., Hermansky, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2009
Subjects
Acoustic measurements
Automatic speech recognition
Availability
Biomedical engineering
Biomedical measurements
Error analysis
Error correction
Frequency
Humans
Pattern Recognition
Speech recognition
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Summary:This paper focuses on resolving a number of issues that appear when the performance of human speech recognition is compared to that of automatic speech recognition. In particular human experimental data suggest that the resulting error is a product of the individual streams. On the other hand, Bayesian combination requires a multiplication of the estimates of prior probabilities and likelihoods. We show that, in principle, there is no discrepancy. The product of errors is a performance measure and human and machine performance may be consistent with this empirically established regularity. The product of probabilities is step in an algorithm to achieve the performance that may or may not be consistent with the product of errors. The main problem is that most of prior discussions failed to distinguish the performance measures from the estimates of the parameters used in the algorithm.
ISBN:9781424423538
1424423538
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2009.4959922