perjury
发表于 2025-3-28 15:08:41
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群岛
发表于 2025-3-28 21:07:39
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Neonatal
发表于 2025-3-29 01:23:54
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configuration
发表于 2025-3-29 03:31:15
Deep Neural Network Sequence-Discriminative Trainingximum mutual information (MMI), boosted MMI (BMMI), minimum phone error (MPE), and minimum Bayes risk (MBR) training criteria, and discuss the practical techniques, including lattice generation, lattice compensation, frame dropping, frame smoothing, and learning rate adjustment, to make DNN sequence-discriminative training effective.
TAG
发表于 2025-3-29 10:14:37
Representation Sharing and Transfer in Deep Neural Networksared and transferred across related tasks through techniques such as multitask and transfer learning. We will use multilingual and crosslingual speech recognition as the main example, which uses a shared-hidden-layer DNN architecture, to demonstrate these techniques.
objection
发表于 2025-3-29 12:32:20
-Pseudo-Differential Operators,raining, and subspace methods. We further show that adaptation in DNNs can bring significant error rate reduction at least for some speech recognition tasks and thus is as important as that in the GMM systems.
maudtin
发表于 2025-3-29 15:44:35
Lewis R. Gordon,LaRose T. Parrisesents a matrix operation upon its children. We describe algorithms to carry out forward computation and gradient calculation in CN and introduce most popular computation node types used in a typical CN.
incision
发表于 2025-3-29 20:57:49
Adaptation of Deep Neural Networksraining, and subspace methods. We further show that adaptation in DNNs can bring significant error rate reduction at least for some speech recognition tasks and thus is as important as that in the GMM systems.
补充
发表于 2025-3-30 03:07:43
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duplicate
发表于 2025-3-30 06:01:58
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