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A Robust Viterbi Algorithm Against Impulsive Noise With Application to Speech Recognition
2006
IEEE Transactions on Audio, Speech, and Language Processing
DRAFT the "best" state sequence that is insensitive to a limited number of corruptions by focusing on finding the best path excluding k worse-performing observations. This is similar to the trimmed-means [16] or robust regression [17] in statistics in that the best path selected would be insensitive to up to k outliers. The labeling of the k worse-performing observations is path dependent. The advantage of the proposed joint approach is that the state dependent likelihoods, used in the process
doi:10.1109/tasl.2006.872592
fatcat:rvkfupsifjepdcgfui4jovo2ju