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Titlebook: DFT-Domain Based Single-Microphone Noise Reduction for Speech Enhancement; Richard C. Hendriks,Timo Gerkmann,Jesper Jensen Book 2013 Sprin

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樓主: SPARK
21#
發(fā)表于 2025-3-25 06:56:38 | 只看該作者
Wolfgang Karl H?rdle,Léopold Simarnd . SNR. The quality of the estimated speech signal therefore heavily depends on the accuracy of the noise PSD estimate. The noise PSD can be underestimated or overestimated. An underestimate of . generally leads to an undersuppression of the noisy speech, and an unnecessarily large amount of resid
22#
發(fā)表于 2025-3-25 09:44:44 | 只看該作者
23#
發(fā)表于 2025-3-25 12:58:32 | 只看該作者
24#
發(fā)表于 2025-3-25 16:16:17 | 只看該作者
25#
發(fā)表于 2025-3-25 20:07:38 | 只看該作者
978-3-031-01436-9Springer Nature Switzerland AG 2013
26#
發(fā)表于 2025-3-26 00:19:44 | 只看該作者
27#
發(fā)表于 2025-3-26 07:41:02 | 只看該作者
1932-121X tance of the various building blocks of such a system. This allows the non-expert DSP practitioner to judge the relevance of each building block and to implemen978-3-031-01436-9978-3-031-02564-8Series ISSN 1932-121X Series E-ISSN 1932-1678
28#
發(fā)表于 2025-3-26 11:25:03 | 只看該作者
29#
發(fā)表于 2025-3-26 14:29:17 | 只看該作者
Speech Presence Probability Estimation, . (.) is a function of the clean speech DFT coefficients, such as the magnitude . (.) = A, P (. |.) is the . SPP,E(. (.)|., .) = 0 [85] and E.|Y, .) is realized by the estimators in Sec. 4.4. For a discussion of the special case . = log (A) see also [84]. In this section we aim at deriving estimato
30#
發(fā)表于 2025-3-26 19:04:30 | 只看該作者
DFT-Domain Based Single-Microphone Noise Reduction for Speech Enhancement
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