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- W1487473780 abstract "Background noise added to speech can decrease the performance of speech segmentation and enhancement. To solve this problem, new methods have been developed in this thesis. First, a new speech segmentation method (ATF-based SONFIN algorithm) is proposed in fixed noise-level environment. This method contains the multiband analysis and a neural fuzzy network, and it achieves higher recognition rate than the TF-based robust algorithm by 5%. In addition, a new speech segmentation method called RTF-based RSONFIN algorithm is proposed for variable noise-level environment. The RTF-based RSONFIN algorithm contains a recurrent neural fuzzy network. This method contains the multiband analysis and achieve higher recognition rate than the TF-based robust algorithm by 12%." @default.
- W1487473780 created "2016-06-24" @default.
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- W1487473780 date "2002-01-01" @default.
- W1487473780 modified "2023-10-09" @default.
- W1487473780 title "Noisy Speech Segmentation/Enhancement with Multiband Analysis and Neural Fuzzy Networks" @default.
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- W1487473780 doi "https://doi.org/10.1007/3-540-45631-7_40" @default.
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