Titlebook: Automatic Speech Recognition; A Deep Learning Appr Dong Yu,Li Deng Book 2015 Springer-Verlag London 2015 Adaptive Training.Automatic Speech

Substitution

碎石头

Deep Neural Networkseech recognition systems, and are the focus of the rest of the book. We depict the architecture of DNNs, describe the popular activation functions and training criteria, illustrate the famous backpropagation algorithm for learning DNN model parameters, and introduce practical tricks that make the training process robust.

Overthrow

CANDY

和平

暗指

M. Pena,E.S. Ibragimova,M.K. Thompsoneech recognition systems, and are the focus of the rest of the book. We depict the architecture of DNNs, describe the popular activation functions and training criteria, illustrate the famous backpropagation algorithm for learning DNN model parameters, and introduce practical tricks that make the training process robust.

narcissism

https://doi.org/10.1007/978-1-349-11724-6ttleneck approach in which DNNs are used as feature extractors. The hidden layers, which are better representation than the raw input feature, are used as features in the GMM systems. We then introduce techniques that fuse the recognition results and frame-level scores of the DNN-HMM hybrid system with that of the GMM-HMM system.

Disk199

Occlusion

Signals and Communication Technologyhttp://image.papertrans.cn/b/image/166448.jpg

Forehead-Lift

https://doi.org/10.1007/978-1-4471-5779-3Adaptive Training; Automatic Speech Recognition; Computational Network; Deep Generative Model; Deep Lear