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- W2608958052 abstract "A new efficient measure for predicting estimation accuracy is proposed and successfully applied to multistream-based unsupervised adaptation of ASR systems to address data uncertainty when the ground-truth is unknown. The proposed measure is an extension of the M-measure, which predicts confidence in the output of a probability estimator by measuring the divergences of probability estimates spaced at specific time intervals. In this study, the M-measure was extended by considering the latent phoneme information, resulting in an improved reliability. Experimental comparisons carried out in a multistream-based ASR paradigm demonstrated that the extended M-measure yields a significant improvement over the original M-measure, especially under narrow-band noise conditions." @default.
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- W2608958052 date "2016-12-01" @default.
- W2608958052 modified "2023-09-28" @default.
- W2608958052 title "A new efficient measure for accuracy prediction and its application to multistream-based unsupervised adaptation" @default.
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- W2608958052 doi "https://doi.org/10.1109/icpr.2016.7899966" @default.
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