Virtual keyboard error correction based on a dynamic spatial model

    公开(公告)号:US11698699B2

    公开(公告)日:2023-07-11

    申请号:US17735937

    申请日:2022-05-03

    Applicant: Google LLC

    CPC classification number: G06F3/04186 G06F3/04886

    Abstract: A method includes detecting a touch input by a user at a position on a virtual keyboard. The method further includes applying a spatial model to map the touch input to one or more first candidate keys of the virtual keyboard, wherein the spatial model maps the touch input to the one or more first candidate keys based on a heatmap of prior touch inputs by the user. The method further includes applying a language model to map the touch input to one or more second candidate keys of the virtual keyboard, wherein the language model maps the touch input to the one or more second candidate keys based on comparing the position of the touch input to one or more predicted next keys. The method further includes selecting a particular key of the one or more first and second candidate keys as indicated by the touch input.

    Virtual keyboard error correction based on a dynamic spatial model

    公开(公告)号:US11347352B2

    公开(公告)日:2022-05-31

    申请号:US17079492

    申请日:2020-10-25

    Applicant: Google LLC

    Abstract: A method includes detecting a touch input by a user at a position on a virtual keyboard. The method further includes applying a spatial model to map the touch input to one or more first candidate keys of the virtual keyboard, wherein the spatial model maps the touch input to the one or more first candidate keys based on a heatmap of prior touch inputs by the user. The method further includes applying a language model to map the touch input to one or more second candidate keys of the virtual keyboard, wherein the language model maps the touch input to the one or more second candidate keys based on comparing the position of the touch input to one or more predicted next keys. The method further includes selecting a particular key of the one or more first and second candidate keys as indicated by the touch input.

    Touch keyboard using a trained model

    公开(公告)号:US11334717B2

    公开(公告)日:2022-05-17

    申请号:US16683895

    申请日:2019-11-14

    Applicant: Google LLC

    Abstract: A computing device outputs for display at a presence-sensitive display, a graphical keyboard comprising a plurality of keys, receives an indication of at least one gesture to select a group of keys of the plurality of keys, and determines at least one characteristic associated with the at least one gesture to select the group of keys of the plurality of keys. The computing device modifies a spatial model based at least in part on the at least one characteristic and determines a candidate word based at least in part on data provided by the spatial model and a language model, wherein the spatial model provides data based at least in part on the indication of the at least one gesture and wherein the language model provides data based at least in part on a lexicon. The computing device outputs for display at the presence-sensitive display, the candidate word.

    Neural Network for Keyboard Input Decoding
    14.
    发明申请

    公开(公告)号:US20200257447A1

    公开(公告)日:2020-08-13

    申请号:US16862628

    申请日:2020-04-30

    Applicant: Google LLC

    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.

    NEURAL NETWORK FOR KEYBOARD INPUT DECODING
    15.
    发明申请

    公开(公告)号:US20190155504A1

    公开(公告)日:2019-05-23

    申请号:US16261640

    申请日:2019-01-30

    Applicant: Google LLC

    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.

    TOUCH KEYBOARD USING LANGUAGE AND SPATIAL MODELS

    公开(公告)号:US20180046612A1

    公开(公告)日:2018-02-15

    申请号:US15795955

    申请日:2017-10-27

    Applicant: Google LLC

    Abstract: A computing device outputs for display at a presence-sensitive display, a graphical keyboard comprising a plurality of keys, receives an indication of at least one gesture to select a group of keys of the plurality of keys, and determines at least one characteristic associated with the at least one gesture to select the group of keys of the plurality of keys. The computing device modifies a spatial model based at least in part on the at least one characteristic and determines a candidate word based at least in part on data provided by the spatial model and a language model, wherein the spatial model provides data based at least in part on the indication of the at least one gesture and wherein the language model provides data based at least in part on a lexicon. The computing device outputs for display at the presence-sensitive display, the candidate word.

    Touch keyboard using a trained model

    公开(公告)号:US11727212B2

    公开(公告)日:2023-08-15

    申请号:US17658227

    申请日:2022-04-06

    Applicant: Google LLC

    Abstract: A computing device outputs for display at a presence-sensitive display, a graphical keyboard comprising a plurality of keys, receives an indication of at least one gesture to select a group of keys of the plurality of keys, and determines at least one characteristic associated with the at least one gesture to select the group of keys of the plurality of keys. The computing device modifies a spatial model based at least in part on the at least one characteristic and determines a candidate word based at least in part on data provided by the spatial model and a language model, wherein the spatial model provides data based at least in part on the indication of the at least one gesture and wherein the language model provides data based at least in part on a lexicon. The computing device outputs for display at the presence-sensitive display, the candidate word.

    Multi-gesture text input prediction

    公开(公告)号:US11379663B2

    公开(公告)日:2022-07-05

    申请号:US17192105

    申请日:2021-03-04

    Applicant: Google LLC

    Abstract: A computing device outputs a keyboard for display, receives an indication of a first gesture to select a first sequence of one or more keys, determines a set of candidate strings based in part on the first sequence of keys, and outputs for display at least one of the set of candidate strings. The computing device receives an indication of a second gesture to select a second sequence of one or more keys, and determines that characters associated with the second sequence of keys are included in a first candidate word based at least in part on the set of candidate strings, or are included in a second candidate word not based on the first sequence of keys. The computing device modifies the set of candidate strings based at least in part on the determination and outputs for display at least one of the modified candidate strings.

    Neural network for keyboard input decoding

    公开(公告)号:US11150804B2

    公开(公告)日:2021-10-19

    申请号:US16862628

    申请日:2020-04-30

    Applicant: Google LLC

    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.

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