中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

8 records (took 0.023 seconds)

    KEYBOARD AUTOMATIC LANGUAGE IDENTIFICATION AND RECONFIGURATION
    1.
    发明申请
    KEYBOARD AUTOMATIC LANGUAGE IDENTIFICATION AND RECONFIGURATION 审中-公开

    公开(公告)号：US20180217749A1

    公开(公告)日：2018-08-02

    申请号：US15422175

    申请日：2017-02-01

    Applicant: Google Inc.

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

    IPC: G06F3/0488 ,  G06F17/27

    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.

    Keyboard automatic language identification and reconfiguration
    3.
    发明授权
    Keyboard automatic language identification and reconfiguration 有权

    公开(公告)号：US10747427B2

    公开(公告)日：2020-08-18

    申请号：US15422175

    申请日：2017-02-01

    Applicant: Google Inc.

    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.

    LEARNING PRONUNCIATIONS FROM ACOUSTIC SEQUENCES
    5.
    发明申请
    LEARNING PRONUNCIATIONS FROM ACOUSTIC SEQUENCES 审中-公开
    从声学序列学习发明

    公开(公告)号：US20160351188A1

    公开(公告)日：2016-12-01

    申请号：US14811939

    申请日：2015-07-29

    Applicant: Google Inc.

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

    IPC: G10L15/187 ,  G10L15/05 ,  G10L15/16 ,  G06F17/27

    CPC classification number: G10L15/187 ,  G06N3/0445 ,  G06N3/084 ,  G10L15/063 ,  G10L15/16 ,  G10L2015/025

    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.

    Abstract translation: 方法，系统和装置，包括在计算机存储介质上编码的用于从声学序列学习发音的计算机程序。 一种方法包括接收声学序列，所述声学序列包括在多个时间步长中的每一个处的相应声学特征表示; 对于通过一个或多个循环神经网络层中的每一个处理声学特征表示的每个时间步骤，以产生反复输出; 使用音素输出层处理时间步长的复现输出，以产生用于时间步长的声学特征表示的音素表示; 以及使用字形输出层处理所述时间步长的复现输出，以生成用于所述时间步长的声学特征表示的图形表示; 并且从每个时间步长处的声音特征表示的音素和图形表示中提取一个或多个单词中的每一个的相应发音。

    COMPRESSED RECURRENT NEURAL NETWORK MODELS
    6.
    发明申请
    COMPRESSED RECURRENT NEURAL NETWORK MODELS 审中-公开

    公开(公告)号：US20170220925A1

    公开(公告)日：2017-08-03

    申请号：US15394617

    申请日：2016-12-29

    Applicant: Google Inc.

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

    IPC: G06N3/04 ,  G06N3/08

    CPC classification number: G06N3/0445 ,  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.

    NEURAL NETWORK FOR KEYBOARD INPUT DECODING
    7.
    发明申请
    NEURAL NETWORK FOR KEYBOARD INPUT DECODING 有权
    键盘输入解码的神经网络

    公开(公告)号：US20160299685A1

    公开(公告)日：2016-10-13

    申请号：US14683861

    申请日：2015-04-10

    Applicant: Google Inc.

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

    IPC: G06F3/0489 ,  G06F3/02 ,  G06F3/023 ,  G06F3/0488 ,  G06F17/27

    CPC classification number: G06F3/04886 ,  G06F3/0219 ,  G06F3/0233 ,  G06F3/0237 ,  G06F3/0482 ,  G06F3/04883 ,  G06F3/04895 ,  G06F17/273 ,  G06F17/276 ,  G06F17/2765 ,  G06N3/0445 ,  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.

    Abstract translation: 在一些示例中，计算设备包括至少一个处理器; 以及至少一个模块，可由所述至少一个处理器操作以：输出用于在输出设备处显示图形键盘; 接收在存在敏感输入设备的位置处检测到的手势的指示，其中所述存在敏感输入设备的位置对应于输出所述图形键盘的输出设备的位置; 基于由所述计算设备使用神经网络处理的手势的至少一个空间特征确定至少一个字符串，其中所述至少一个空间特征指示所述手势的至少一个物理属性; 并且至少部分地基于使用所述神经网络的所述手势的所述至少一个空间特征的处理来输出所述至少一个字符串，用于在所述输出设备处显示。

    Neural network for keyboard input decoding
    8.
    发明授权
    Neural network for keyboard input decoding 有权

    公开(公告)号：US10248313B2

    公开(公告)日：2019-04-02

    申请号：US15473010

    申请日：2017-03-29

    Applicant: Google Inc.

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

    IPC: G06F3/02 ,  G06F3/0488 ,  G06F17/27 ,  G06F3/023 ,  G06F3/0489 ,  G06N3/04 ,  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.

Patent Agency Ranking