Speaker recognition with hybrid features from a deep belief network
Learning representation from audio data has shown advantages over the handcrafted features such as mel-frequency cepstral coefficients (MFCCs) in many audio applications. In most of the representation learning approaches, the connectionist systems have been used to learn and extract latent features...
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Veröffentlicht in: | Neural computing & applications 2018-03, Vol.29 (6), p.13-19 |
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