Jan 25, 2018 · In this paper, we argue that to apply senone i-vectors in noisy environments, it is important to robustify the phonetically discriminative ...
In this paper, we argue that to apply senone i-vectors in noisy environments, it is important to robustify the phonetically discriminative acoustic features.
This paper explores and extends our early work [36] on using DNNs for extracting phonetically discriminative and noise robust bottleneck features from noisy ...
This work proposes a deep architecture formed by stacking a deep belief network on top of a denoising autoencoder–deep neural network (DAE–DNN), ...
The proposed method addresses noise robustness in two perspectives: (1) denoising the MFCC vectors through the DAE and (2) extracting noise robust bottleneck ( ...
PDF | On Oct 1, 2016, Zhili Tan and others published Senone I-vectors for robust speaker verification | Find, read and cite all the research you need on ...
The proposed method addresses noise robustness in two perspectives: (1) denoising the MFCC vectors through the DAE and (2) extracting noise robust bottleneck ( ...
The proposed method addresses noise robustness in two perspectives: (1) denoising the MFCC vectors through the DAE and (2) extracting noise robust bottleneck ( ...
The denoising autoencoder improves noise robustness. • The original NIST 12 CC4 evaluation set already contains noisy speech. Experiments on only clean speech ...
Missing: Verification. | Show results with:Verification.
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Denoised senone i-vectors for robust speaker verification. Z Tan, MW Mak, BKW Mak, Y Zhu. IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (4) ...