Machine learning model with depth processing units

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United States of America

PATENT NO 12086704
SERIAL NO

17518535

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Abstract

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Representative embodiments disclose machine learning classifiers used in scenarios such as speech recognition, image captioning, machine translation, or other sequence-to-sequence embodiments. The machine learning classifiers have a plurality of time layers, each layer having a time processing block and a depth processing block. The time processing block is a recurrent neural network such as a Long Short Term Memory (LSTM) network. The depth processing blocks can be an LSTM network, a gated Deep Neural Network (DNN) or a maxout DNN. The depth processing blocks account for the hidden states of each time layer and uses summarized layer information for final input signal feature classification. An attention layer can also be used between the top depth processing block and the output layer.

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Patent Owner(s)

Patent OwnerAddress
MICROSOFT TECHNOLOGY LICENSING LLCONE MICROSOFT WAY REDMOND WA 98052

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Gong, Yifan Sammamish, US 111 2806
Li, Jinyu Redmond, US 124 2102
Liu, Changliang Bothell, US 12 15
Lu, Liang Redmond, US 118 2257

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