公开(公告)号：US20210089916A1

公开(公告)日：2021-03-25

申请号：US17112966

申请日：2020-12-04

Applicant: Google LLC

Inventor： Ouais Alsharif ,  Rohit Prakash Prabhavalkar ,  Ian C. McGraw ,  Antoine Jean Bruguier

IPC: G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing a compressed recurrent neural network (RNN). One of the systems includes a compressed RNN, the compressed RNN comprising a plurality of recurrent layers, wherein each of the recurrent layers has a respective recurrent weight matrix and a respective inter-layer weight matrix, and wherein at least one of recurrent layers is compressed such that a respective recurrent weight matrix of the compressed layer is defined by a first compressed weight matrix and a projection matrix and a respective inter-layer weight matrix of the compressed layer is defined by a second compressed weight matrix and the projection matrix.

公开(公告)号：US11573698B2

公开(公告)日：2023-02-07

申请号：US17469622

申请日：2021-09-08

Applicant: Google LLC

Inventor： Shumin Zhai ,  Thomas Breuel ,  Ouais Alsharif ,  Yu Ouyang ,  Francoise Beaufays ,  Johan Schalkwyk

IPC: G06F3/02 ,  G06F3/04886 ,  G06N3/04 ,  G06F40/232 ,  G06F40/274 ,  G06F40/279 ,  G06F3/023 ,  G06F3/04895 ,  G06F3/0482 ,  G06F3/04883 ,  G06N3/08

Abstract: In some examples, a computing device includes at least one processor; and at least one module, operable by the at least one processor to: output, for display at an output device, a graphical keyboard; receive an indication of a gesture detected at a location of a presence-sensitive input device, wherein the location of the presence-sensitive input device corresponds to a location of the output device that outputs the graphical keyboard; determine, based on at least one spatial feature of the gesture that is processed by the computing device using a neural network, at least one character string, wherein the at least one spatial feature indicates at least one physical property of the gesture; and output, for display at the output device, based at least in part on the processing of the at least one spatial feature of the gesture using the neural network, the at least one character string.

公开(公告)号：US11508147B2

公开(公告)日：2022-11-22

申请号：US16812154

申请日：2020-03-06

Applicant: Google LLC

Inventor： Jonathon Shlens ,  Vijay Vasudevan ,  Jiquan Ngiam ,  Wei Han ,  Zhifeng Chen ,  Brandon Chauloon Yang ,  Benjamin James Caine ,  Zhengdong Zhang ,  Christoph Sprunk ,  Ouais Alsharif ,  Junhua Mao ,  Chen Wu

IPC: G06V20/10 ,  G06T17/00 ,  G01S17/89 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing data generated by a sensing system that rotationally senses an environment. In one aspect, a method comprises partitioning a predetermined period of time into a plurality of sub-periods, wherein the predetermined period of time is a period of time for which data generated by the sensing system constitutes a complete rotational sensing of the environment; for each sub-period: receiving current data generated by the sensing system during the sub-period and characterizing a respective partial scene of the environment; processing the current data using an object detection neural network to generate a current object detection output that is specific to the respective partial scene of the environment.

公开(公告)号：US20200371686A1

公开(公告)日：2020-11-26

申请号：US16989420

申请日：2020-08-10

Applicant: Google LLC

Inventor： Ouais Alsharif ,  Peter Ciccotto ,  Francoise Beaufays ,  Dragan Zivkovic

IPC: G06F3/0488 ,  G06F3/023 ,  G06F40/263 ,  G06F40/274

Abstract: A keyboard is described that determines, using a first decoder and based on a selection of keys of a graphical keyboard, text. Responsive to determining that a characteristic of the text satisfies a threshold, a model of the keyboard identifies the target language of the text, and determines whether the target language is different than a language associated with the first decoder. If the target language of the text is not different than the language associated with the first decoder, the keyboard outputs, for display, an indication of first candidate words determined by the first decoder from the text. If the target language of the text is different: the keyboard enables a second decoder, where a language associated with the second decoder matches the target language of the text, and outputs, for display, an indication of second candidate words determined by the second decoder from the text.

公开(公告)号：US10671281B2

公开(公告)日：2020-06-02

申请号：US16261640

申请日：2019-01-30

Applicant: Google LLC

Inventor： Shumin Zhai ,  Thomas Breuel ,  Ouais Alsharif ,  Yu Ouyang ,  Francoise Beaufays ,  Johan Schalkwyk

IPC: G06F3/02 ,  G06F3/0488 ,  G06N3/04 ,  G06F40/232 ,  G06F40/274 ,  G06F40/279 ,  G06F3/023 ,  G06F3/0489 ,  G06F3/0482 ,  G06N3/08

Abstract: In some examples, a computing device includes at least one processor; and at least one module, operable by the at least one processor to: output, for display at an output device, a graphical keyboard; receive an indication of a gesture detected at a location of a presence-sensitive input device, wherein the location of the presence-sensitive input device corresponds to a location of the output device that outputs the graphical keyboard; determine, based on at least one spatial feature of the gesture that is processed by the computing device using a neural network, at least one character string, wherein the at least one spatial feature indicates at least one physical property of the gesture; and output, for display at the output device, based at least in part on the processing of the at least one spatial feature of the gesture using the neural network, the at least one character string.

公开(公告)号：US10127904B2

公开(公告)日：2018-11-13

申请号：US14811939

申请日：2015-07-29

Applicant: Google LLC

Inventor： Kanury Kanishka Rao ,  Francoise Beaufays ,  Hasim Sak ,  Ouais Alsharif

IPC: G10L15/00 ,  G10L15/187 ,  G10L15/06 ,  G06N3/04 ,  G06N3/08 ,  G10L15/16 ,  G10L15/02

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for learning pronunciations from acoustic sequences. One method includes receiving an acoustic sequence, the acoustic sequence comprising a respective acoustic feature representation at each of a plurality of time steps; for each of the time steps processing the acoustic feature representation through each of one or more recurrent neural network layers to generate a recurrent output; processing the recurrent output for the time step using a phoneme output layer to generate a phoneme representation for the acoustic feature representation for the time step; and processing the recurrent output for the time step using a grapheme output layer to generate a grapheme representation for the acoustic feature representation for the time step; and extracting, from the phoneme and grapheme representations for the acoustic feature representations at each time step, a respective pronunciation for each of one or more words.