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- W2106981472 abstract "Separating speech from acoustic interference is a very challenging task. In particular, no system successfully addresses the separation of unvoiced speech. Fricatives and affricates are two main categories of consonants that contain a significant amount of unvoiced signal. We propose a novel system that separates fricatives and affricates from non-speech interference. The system first decomposes the input mixture into segments, each of which contains signal mainly from one source. Then it detects segments dominated by unvoiced portions of fricatives and affricates with a feature-based Bayesian classifier, and groups these segments with voiced speech separated by a previous system. The proposed system is evaluated with various types of interference and produces promising results." @default.
- W2106981472 created "2016-06-24" @default.
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- W2106981472 date "2006-10-11" @default.
- W2106981472 modified "2023-09-26" @default.
- W2106981472 title "Separation of Fricatives and Affricates" @default.
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- W2106981472 doi "https://doi.org/10.1109/icassp.2005.1415310" @default.
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