公开(公告)号：US20180075343A1

公开(公告)日：2018-03-15

申请号：US15697407

申请日：2017-09-06

申请人： Google Inc.

发明人： Aaron Gerard Antonius van den Oord ,  Sander Etienne Lea Dieleman ,  Nal Emmerich Kalchbrenner ,  Karen Simonyan ,  Oriol Vinyals ,  Lasse Espeholt

IPC分类号： G06N3/04 ,  G06F17/27 ,  G10L25/30 ,  G10L15/16 ,  G10L13/08

CPC分类号： G06N3/0472 ,  G06F17/18 ,  G06F17/2765 ,  G06F17/2818 ,  G06N3/0445 ,  G06N3/0454 ,  G06N3/084 ,  G10H2250/311 ,  G10L13/04 ,  G10L13/086 ,  G10L15/16 ,  G10L25/30

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing sequences using convolutional neural networks. One of the methods includes, for each of the time steps: providing a current sequence of audio data as input to a convolutional subnetwork, wherein the current sequence comprises the respective audio sample at each time step that precedes the time step in the output sequence, and wherein the convolutional subnetwork is configured to process the current sequence of audio data to generate an alternative representation for the time step; and providing the alternative representation for the time step as input to an output layer, wherein the output layer is configured to: process the alternative representation to generate an output that defines a score distribution over a plurality of possible audio samples for the time step.

公开(公告)号：US20180025257A1

公开(公告)日：2018-01-25

申请号：US15721089

申请日：2017-09-29

申请人： Google Inc.

发明人： Aaron Gerard Antonius van den Oord ,  Nal Emmerich Kalchbrenner ,  Karen Simonyan

IPC分类号： G06K9/66 ,  H04N19/52 ,  G06K9/46 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

CPC分类号： G06K9/66 ,  G06K9/4652 ,  G06K9/623 ,  G06N3/04 ,  G06N3/0445 ,  G06N3/0454 ,  G06N3/08 ,  G06N3/084 ,  H04N19/172 ,  H04N19/182 ,  H04N19/186 ,  H04N19/50 ,  H04N19/52

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating images using neural networks. One of the methods includes generating the output image pixel by pixel from a sequence of pixels taken from the output image, comprising, for each pixel in the output image, generating a respective score distribution over a discrete set of possible color values for each of the plurality of color channels.

公开(公告)号：US20170228642A1

公开(公告)日：2017-08-10

申请号：US15395553

申请日：2016-12-30

申请人： Google Inc.

发明人： Ivo Danihelka ,  Nal Emmerich Kalchbrenner ,  Gregory Duncan Wayne ,  Benigno Uría-Martínez ,  Alexander Benjamin Graves

IPC分类号： G06N3/08 ,  G06N3/04

CPC分类号： G06N3/08 ,  G06N3/04 ,  G06N3/0445

摘要： Systems, methods, and apparatus, including computer programs encoded on a computer storage medium, related to associative long short-term memory (LSTM) neural network layers configured to maintain N copies of an internal state for the associative LSTM layer, N being an integer greater than one. In one aspect, a system includes a recurrent neural network including an associative LSTM layer, wherein the associative LSTM layer is configured to, for each time step, receive a layer input, update each of the N copies of the internal state using the layer input for the time step and a layer output generated by the associative LSTM layer for a preceding time step, and generate a layer output for the time step using the N updated copies of the internal state.