公开(公告)号：US11080591B2

公开(公告)日：2021-08-03

申请号：US15697407

申请日：2017-09-06

Applicant: DeepMind Technologies Limited

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

IPC: G06N3/04 ,  G10L15/16 ,  G10L13/08 ,  G10L25/30 ,  G10L13/04 ,  G06N3/08 ,  G06F40/44 ,  G06F40/279 ,  G06F17/18

Abstract: 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：US20200342183A1

公开(公告)日：2020-10-29

申请号：US16927267

申请日：2020-07-13

Applicant: DeepMind Technologies Limited

Inventor： Nal Emmerich Kalchbrenner ,  Karen Simonyan ,  Lasse Espeholt

IPC: G06F40/58 ,  G06N3/04 ,  G06F40/44 ,  G06N3/08 ,  G10L15/197

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for language modeling. In one aspect, a system comprises: a masked convolutional decoder neural network that comprises a plurality of masked convolutional neural network layers and is configured to generate a respective probability distribution over a set of possible target embeddings at each of a plurality of time steps; and a modeling engine that is configured to use the respective probability distribution generated by the decoder neural network at each of the plurality of time steps to estimate a probability that a string represented by the target embeddings corresponding to the plurality of time steps belongs to the natural language.

公开(公告)号：US11868894B2

公开(公告)日：2024-01-09

申请号：US18149771

申请日：2023-01-04

Applicant: DeepMind Technologies Limited

Inventor： Hubert Josef Soyer ,  Lasse Espeholt ,  Karen Simonyan ,  Yotam Doron ,  Vlad Firoiu ,  Volodymyr Mnih ,  Koray Kavukcuoglu ,  Remi Munos ,  Thomas Ward ,  Timothy James Alexander Harley ,  Iain Robert Dunning

IPC: G06N3/08 ,  G06N3/045

CPC classification number: G06N3/08 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network used to select actions to be performed by an agent interacting with an environment. In one aspect, a system comprises a plurality of actor computing units and a plurality of learner computing units. The actor computing units generate experience tuple trajectories that are used by the learner computing units to update learner action selection neural network parameters using a reinforcement learning technique. The reinforcement learning technique may be an off-policy actor critic reinforcement learning technique.

公开(公告)号：US20210342670A1

公开(公告)日：2021-11-04

申请号：US17375250

申请日：2021-07-14

Applicant: DeepMind Technologies Limited

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

IPC: G06N3/04 ,  G10L15/16 ,  G10L13/08 ,  G10L25/30 ,  G10L13/04 ,  G06N3/08 ,  G06F40/44 ,  G06F40/279

Abstract: 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：US10733390B2

公开(公告)日：2020-08-04

申请号：US16434459

申请日：2019-06-07

Applicant: DeepMind Technologies Limited

Inventor： Nal Emmerich Kalchbrenner ,  Karen Simonyan ,  Lasse Espeholt

IPC: G06F40/58 ,  G06N3/04 ,  G06F40/44 ,  G06N3/08 ,  G10L15/197

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for language modeling. In one aspect, a system comprises: a masked convolutional decoder neural network that comprises a plurality of masked convolutional neural network layers and is configured to generate a respective probability distribution over a set of possible target embeddings at each of a plurality of time steps; and a modeling engine that is configured to use the respective probability distribution generated by the decoder neural network at each of the plurality of time steps to estimate a probability that a string represented by the target embeddings corresponding to the plurality of time steps belongs to the natural language.

公开(公告)号：US20190286708A1

公开(公告)日：2019-09-19

申请号：US16434459

申请日：2019-06-07

Applicant: DeepMind Technologies Limited

Inventor： Nal Emmerich Kalchbrenner ,  Karen Simonyan ,  Lasse Espeholt

IPC: G06F17/28 ,  G10L15/197 ,  G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neural machine translation. In one aspect, a system is configured to receive an input sequence of source embeddings representing a source sequence of words in a source natural language and to generate an output sequence of target embeddings representing a target sequence of words that is a translation of the source sequence into a target natural language, the system comprising: a dilated convolutional neural network configured to process the input sequence of source embeddings to generate an encoded representation of the source sequence, and a masked dilated convolutional neural network configured to process the encoded representation of the source sequence to generate the output sequence of target embeddings.

公开(公告)号：US20180329897A1

公开(公告)日：2018-11-15

申请号：US16032971

申请日：2018-07-11

Applicant: DeepMind Technologies Limited

Inventor： Nal Emmerich Kalchbrenner ,  Karen Simonyan ,  Lasse Espeholt

IPC: G06F17/28 ,  G06N3/04 ,  G06N3/08 ,  G10L15/197

CPC classification number: G06F17/289 ,  G06F17/2818 ,  G06N3/0454 ,  G06N3/0472 ,  G06N3/084 ,  G10L15/197

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neural machine translation. In one aspect, a system is configured to receive an input sequence of source embeddings representing a source sequence of words in a source natural language and to generate an output sequence of target embeddings representing a target sequence of words that is a translation of the source sequence into a target natural language, the system comprising: a dilated convolutional neural network configured to process the input sequence of source embeddings to generate an encoded representation of the source sequence, and a masked dilated convolutional neural network configured to process the encoded representation of the source sequence to generate the output sequence of target embeddings.

公开(公告)号：US11948066B2

公开(公告)日：2024-04-02

申请号：US17375250

申请日：2021-07-14

Applicant: DeepMind Technologies Limited

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

IPC: G06N3/04 ,  G06F40/279 ,  G06F40/44 ,  G06N3/044 ,  G06N3/045 ,  G06N3/047 ,  G06N3/084 ,  G10L13/04 ,  G10L13/08 ,  G10L15/16 ,  G10L25/30 ,  G06F17/18

CPC classification number: G06N3/047 ,  G06F40/279 ,  G06F40/44 ,  G06N3/044 ,  G06N3/045 ,  G06N3/084 ,  G10L13/04 ,  G10L13/086 ,  G10L15/16 ,  G10L25/30 ,  G06F17/18 ,  G10H2250/311

Abstract: 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：US11593646B2

公开(公告)日：2023-02-28

申请号：US16767049

申请日：2019-02-05

Applicant: DeepMind Technologies Limited

Inventor： Hubert Josef Soyer ,  Lasse Espeholt ,  Karen Simonyan ,  Yotam Doron ,  Vlad Firoiu ,  Volodymyr Mnih ,  Koray Kavukcuoglu ,  Remi Munos ,  Thomas Ward ,  Timothy James Alexander Harley ,  Iain Robert Dunning

IPC: G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network used to select actions to be performed by an agent interacting with an environment. In one aspect, a system comprises a plurality of actor computing units and a plurality of learner computing units. The actor computing units generate experience tuple trajectories that are used by the learner computing units to update learner action selection neural network parameters using a reinforcement learning technique. The reinforcement learning technique may be an off-policy actor critic reinforcement learning technique.

公开(公告)号：US11069345B2

公开(公告)日：2021-07-20

申请号：US16719424

申请日：2019-12-18

Applicant: DeepMind Technologies Limited

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

IPC: G10L15/16 ,  G06N3/04 ,  G06N3/08 ,  G10L15/02 ,  G10L15/22

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing speech recognition by generating a neural network output from an audio data input sequence, where the neural network output characterizes words spoken in the audio data input sequence. One of the methods includes, for each of the audio data inputs, providing a current audio data input sequence that comprises the audio data input and the audio data inputs preceding the audio data input in the audio data input sequence to a convolutional subnetwork comprising a plurality of dilated convolutional neural network layers, wherein the convolutional subnetwork is configured to, for each of the plurality of audio data inputs: receive the current audio data input sequence for the audio data input, and process the current audio data input sequence to generate an alternative representation for the audio data input.