Mikyong Ji

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—In this letter, a probabilistic class histogram equalization method is proposed to compensate for an acoustic mismatch in noise robust speech recognition. The proposed method aims not only to compensate for the acoustic mismatch between training and test environments but also to reduce the limitations of the conventional histogram equalization. It utilizes(More)
— With the aim of achieving the best possible speaker identification rate in a distant-talking environment, we developed a multiple microphone-based text-independent speaker identification system using soft channel selection. The system selects and combines the identification results based on the reliability of an individual channel result using a single(More)
SUMMARY Recently, many techniques have been proposed to improve speaker identification in noise environments. Among these techniques , we consider the feature recombination technique for the multi-band approach in noise robust speaker identification. The conventional feature recombination technique is very effective in the band-limited noise condition , but(More)
In speaker Identification System, the goal is to determine which one of the groups of an unknown voice which best matches with one of the input voices. The field of speaker identification has recently seen significant advancement, but improvements have tended on near field speech, ignoring the more realistic setting of far field instrumented speakers. In(More)
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