公开(公告)号：US20240220527A1

公开(公告)日：2024-07-04

申请号：US18606458

申请日：2024-03-15

Applicant: Google LLC

Inventor： Gregory Sean Corrado ,  Tomas Mikolov ,  Samuel Bengio ,  Yoram Singer ,  Jonathon Shlens ,  Andrea L. Frome ,  Jeffrey Adgate Dean ,  Mohammad Norouzi

IPC: G06F16/35 ,  G06F16/50

CPC classification number: G06F16/35 ,  G06F16/50

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying data objects. One of the methods includes obtaining data that associates each term in a vocabulary of terms with a respective high-dimensional representation of the term; obtaining classification data for a data object, wherein the classification data includes a respective score for each of a plurality of categories, and wherein each of the categories is associated with a respective category label; computing an aggregate high-dimensional representation for the data object from high-dimensional representations for the category labels associated with the categories and the respective scores; identifying a first term in the vocabulary of terms having a high-dimensional representation that is closest to the aggregate high-dimensional representation; and selecting the first term as a category label for the data object.

公开(公告)号：US20240038245A1

公开(公告)日：2024-02-01

申请号：US18485069

申请日：2023-10-11

Applicant: Google LLC

Inventor： Georg Heigold ,  Samuel Bengio ,  Ignacio Lopez Moreno

IPC: G10L17/18 ,  G10L17/04 ,  G10L17/02

CPC classification number: G10L17/18 ,  G10L17/04 ,  G10L17/02

Abstract: This document generally describes systems, methods, devices, and other techniques related to speaker verification, including (i) training a neural network for a speaker verification model, (ii) enrolling users at a client device, and (iii) verifying identities of users based on characteristics of the users' voices. Some implementations include a computer-implemented method. The method can include receiving, at a computing device, data that characterizes an utterance of a user of the computing device. A speaker representation can be generated, at the computing device, for the utterance using a neural network on the computing device. The neural network can be trained based on a plurality of training samples that each: (i) include data that characterizes a first utterance and data that characterizes one or more second utterances, and (ii) are labeled as a matching speakers sample or a non-matching speakers sample.

公开(公告)号：US20220004849A1

公开(公告)日：2022-01-06

申请号：US17295561

申请日：2019-11-20

Applicant: Google LLC

Inventor： Zhourong Chen ,  Yang Li ,  Samuel Bengio ,  Si Si

IPC: G06N3/04 ,  G06N3/08 ,  G06T5/20 ,  G06T5/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using neural networks. One of the methods includes receiving a network input; processing the network input through a gater neural network to generate a gating vector that includes a respective value for each of a plurality of filters; determining, from the gating vector and for each of the plurality of filters, whether the filter is active or inactive; and processing the network input through the main convolutional neural network to generate an image processing output, comprising, for each convolutional layer in the first plurality of convolutional layers: receiving an input feature map for the convolutional layer; and generating an output feature map, the generating comprising: for each filter of the convolutional layer that is inactive: setting the output channel for the filter to have all zero elements.

公开(公告)号：US20210366463A1

公开(公告)日：2021-11-25

申请号：US17391799

申请日：2021-08-02

Applicant: Google LLC

Inventor： Samuel Bengio ,  Yuxuan Wang ,  Zongheng Yang ,  Zhifeng Chen ,  Yonghui Wu ,  Ioannis Agiomyrgiannakis ,  Ron J. Weiss ,  Navdeep Jaitly ,  Ryan M. Rifkin ,  Robert Andrew James Clark ,  Quoc V. Le ,  Russell J. Ryan ,  Ying Xiao

IPC: G10L13/08 ,  G06N3/08 ,  G10L25/18 ,  G10L25/30 ,  G10L13/04 ,  G06N3/04 ,  G10L15/16

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.

公开(公告)号：US20200098350A1

公开(公告)日：2020-03-26

申请号：US16696101

申请日：2019-11-26

Applicant: Google LLC

Inventor： Samuel Bengio ,  Yuxuan Wang ,  Zongheng Yang ,  Zhifeng Chen ,  Yonghui Wu ,  Ioannis Agiomyrgiannakis ,  Ron J. Weiss ,  Navdeep Jaitly ,  Ryan M. Rifkin ,  Robert Andrew James Clark ,  Quoc V. Le ,  Russell J. Ryan ,  Ying Xiao

IPC: G10L13/08 ,  G10L15/16 ,  G06N3/08 ,  G06N3/04 ,  G10L13/04 ,  G10L25/30 ,  G10L25/18

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.

公开(公告)号：US11829860B2

公开(公告)日：2023-11-28

申请号：US17679625

申请日：2022-02-24

Applicant: Google LLC

Inventor： Oriol Vinyals ,  Samuel Bengio

IPC: G06N3/04 ,  G06N3/044 ,  G06N3/045

CPC classification number: G06N3/044 ,  G06N3/045

Abstract: In one aspect, this specification describes a recurrent neural network system implemented by one or more computers that is configured to process input sets to generate neural network outputs for each input set. The input set can be a collection of multiple inputs for which the recurrent neural network should generate the same neural network output regardless of the order in which the inputs are arranged in the collection. The recurrent neural network system can include a read neural network, a process neural network, and a write neural network. In another aspect, this specification describes a system implemented as computer programs on one or more computers in one or more locations that is configured to train a recurrent neural network that receives a neural network input and sequentially emits outputs to generate an output sequence for the neural network input.

公开(公告)号：US11803747B2

公开(公告)日：2023-10-31

申请号：US16878720

申请日：2020-05-20

Applicant: Google LLC

Inventor： Samuel Bengio ,  Mohammad Norouzi ,  Benoit Steiner ,  Jeffrey Adgate Dean ,  Hieu Hy Pham ,  Azalia Mirhoseini ,  Quoc V. Le ,  Naveen Kumar ,  Yuefeng Zhou ,  Rasmus Munk Larsen

IPC: G06N3/08 ,  G06N5/04 ,  G06N3/10 ,  G06N3/044 ,  G06N3/045

CPC classification number: G06N3/08 ,  G06N3/044 ,  G06N3/045 ,  G06N3/105 ,  G06N5/04

Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices is described. The method includes receiving data specifying a machine learning model to be placed for distributed processing on multiple hardware devices; generating, from the data, a sequence of operation embeddings, each operation embedding in the sequence characterizing respective operations necessary to perform the processing of the machine learning model; processing the sequence of operation embeddings using a placement recurrent neural network in accordance with first values of a plurality network parameters of the placement recurrent neural network to generate a network output that defines a placement of the operations characterized by the operation embeddings in the sequence across the plurality of devices; and scheduling the machine learning model for processing by the multiple hardware devices by placing the operations on the multiple devices according to the placement defined by the network output.

公开(公告)号：US20200286468A1

公开(公告)日：2020-09-10

申请号：US16879322

申请日：2020-05-20

Applicant: Google LLC

Inventor： Samuel Bengio ,  Mirko Visontai ,  Christopher Walter George Thornton ,  Tara N. Sainath ,  Ehsan Variani ,  Izhak Shafran ,  Michiel A.u. Bacchiani

IPC: G10L15/16 ,  G10L15/02 ,  G10H1/00 ,  G10L19/02

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech recognition using complex linear projection are disclosed. In one aspect, a method includes the actions of receiving audio data corresponding to an utterance. The method further includes generating frequency domain data using the audio data. The method further includes processing the frequency domain data using complex linear projection. The method further includes providing the processed frequency domain data to a neural network trained as an acoustic model. The method further includes generating a transcription for the utterance that is determined based at least on output that the neural network provides in response to receiving the processed frequency domain data.

公开(公告)号：US20200042866A1

公开(公告)日：2020-02-06

申请号：US16538712

申请日：2019-08-12

Applicant: Google LLC

Inventor： Samuel Bengio ,  Oriol Vinyals ,  Alexander Toshkov Toshev ,  Dumitru Erhan

IPC: G06N3/04 ,  G06F17/28

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating descriptions of input images. One of the methods includes obtaining an input image; processing the input image using a first neural network to generate an alternative representation for the input image; and processing the alternative representation for the input image using a second neural network to generate a sequence of a plurality of words in a target natural language that describes the input image.

公开(公告)号：US20200012905A1

公开(公告)日：2020-01-09

申请号：US16576321

申请日：2019-09-19

Applicant: Google LLC

Inventor： Samuel Bengio ,  Jeffrey Adgate Dean ,  Quoc V. Le ,  Jonathon Shlens ,  Yoram Singer

IPC: G06K9/72 ,  G06N20/00 ,  G06N7/00 ,  G06K9/00 ,  G06K9/62

Abstract: Systems and techniques are disclosed for labeling objects within an image. The objects may be labeled by selecting an option from a plurality of options such that each option is a potential label for the object. An option may have an option score associated with. Additionally, a relation score may be calculated for a first option and a second option corresponding to a second object in an image. The relation score may be based on a frequency, probability, or observance corresponding to the co-occurrence of text associated with the first option and the second option in a text corpus such as the World Wide Web. An option may be selected as a label for an object based on a global score calculated based at least on an option score and relation score associated with the option.