Invention Grant
US09177550B2 Conservatively adapting a deep neural network in a recognition system
有权
在识别系统中保守地适应深层神经网络
- Patent Title: Conservatively adapting a deep neural network in a recognition system
- Patent Title (中): 在识别系统中保守地适应深层神经网络
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Application No.: US13786470Application Date: 2013-03-06
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Publication No.: US09177550B2Publication Date: 2015-11-03
- Inventor: Dong Yu , Kaisheng Yao , Hang Su , Gang Li , Frank Seide
- Applicant: Microsoft Corporation
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agent Sandy Swain; Judy Yee; Micky Minhas
- Main IPC: G10L15/16
- IPC: G10L15/16 ; G06N3/04 ; G06N3/08 ; G10L15/20 ; G10L15/07

Abstract:
Various technologies described herein pertain to conservatively adapting a deep neural network (DNN) in a recognition system for a particular user or context. A DNN is employed to output a probability distribution over models of context-dependent units responsive to receipt of captured user input. The DNN is adapted for a particular user based upon the captured user input, wherein the adaption is undertaken conservatively such that a deviation between outputs of the adapted DNN and the unadapted DNN is constrained.
Public/Granted literature
- US20140257803A1 CONSERVATIVELY ADAPTING A DEEP NEURAL NETWORK IN A RECOGNITION SYSTEM Public/Granted day:2014-09-11
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