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- W2575447002 abstract "Speaker diarization is a significant part of many applications in today's fast growing user-end software and technologies. In the last decade, speaker diarization has attracted significant research effort, however most of the speaker diarization methods deeply rely on statistical models which become unreliable in case of short utterances diarization and in noisy conditions. In this paper, we introduce a speaker diarization system which is based on the Locally Linear Embedding (LLE). The LLE enables to extract the inherent structure of the data and thus provide better clustering. Experimental results show error rates lower than 10% and improved stability in comparison with a conventional speaker diarization method." @default.
- W2575447002 created "2017-01-26" @default.
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- W2575447002 date "2016-11-01" @default.
- W2575447002 modified "2023-09-24" @default.
- W2575447002 title "Speaker diarization based on locally linear embedding" @default.
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- W2575447002 doi "https://doi.org/10.1109/icsee.2016.7806168" @default.
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