Google Inc.

Nec Corporation

Keisuke Kuroyanagi

Satoshi Kataoka

Shumin Zhai

Yu Ouyang

Ciprian Ioan Chelba

Xiaojun Bi

Ken Wakasa

Hajime Kawamura

A computing device is described that outputs, for display, a graphical keyboard comprising a plurality of keys. The computing device receives, an indication of a gesture detected at a presence-sensitive input device. The computing device determines, based at least in part on the indication of the gesture and at least one characteristic of the gesture, one or more keys from the plurality of keys. The computing device determines a character string based on the one or more keys from the plurality of keys. In response to determining that the character string is not included in a lexicon and a spatial model probability associated with the one or more keys from the plurality of keys exceeds a probability threshold, the computing device outputs, for display, the character string.

Gesture keyboard input of non-dictionary character strings

In one example, a method includes outputting, at a presence-sensitive display operatively coupled to a computing device, a graphical keyboard comprising a plurality of keys and receiving an indication of a gesture to select a group of keys of the plurality of keys. The method may further include determining, in response to the indication, a candidate word based at least in part on the group of keys. The method may further include determining a group of alignment points traversed by the gesture and respective cost values for each of at least two keys of the plurality of keys. The method may further include comparing the respective cost values for at least each of at least two keys of the plurality of keys to determine a combination of keys having a combined cost value and outputting the candidate word that is based on the respective cost values.

Incremental feature-based gesture-keyboard decoding

In one example, a computing device may receive an indication of a user input entered at a location of a presence-sensitive screen and defines a group of gesture events based at least in part on the indication. The computing device may determine a density of a portion of the group of gesture events. The density may indicate, for example, a quantity of gesture events associated with a region of the presence-sensitive screen over a time duration. In response to determining that the density satisfies a threshold, the computing device may modify the group of gesture events based at least in part on the density.

Density-based filtering of gesture events associated with a user interface of a computing device

In one example, a method includes outputting, by a computing device and for display, a graphical keyboard comprising a group of keys. The method may further include receiving an indication of a first portion of a gesture to select a first key, and determining, based at least in part on the first key, one or more predicted next characters. The method may further include determining a path from a first location of the graphical keyboard to a second location of the graphical keyboard, the first location corresponding to the first key, the second location corresponding to one of the one or more predicted next characters. The method may further include comparing a second portion of the gesture with the determined path, and selecting, based at least in part on the comparison, the one of the one or more predicted next characters.

Gesture-keyboard decoding using gesture path deviation

In one example, a method includes outputting, by a computing device and for display, a graphical keyboard comprising a plurality of keys. The method may also include receiving, by the computing device, an indication of a gesture detected at a presence-sensitive input device. The method may also include determining, by the computing device and based on a plurality of features associated with the gesture, a degree of precision of the gesture. The method may also include modifying, by the computing device and based at least in part on the degree of precision, a probability that the gesture indicates at least one key of the plurality of keys. The method may also include outputting, by the computing device and for display, a candidate word that is based at least in part on the probability that the gesture indicates at least one key of the plurality of keys.

Decoding imprecise gestures for gesture-keyboards

In one example, a computing device may include at least one processor that outputs a graphical keyboard. The at least one processor may determine a selection of one or more keys; and determine a character string based on the one or more keys in the selection, wherein the character string is not included in a vocabulary used by the computing device to identify character strings. The at least one processor may, in response to determining that the character string is not included in the vocabulary used by the computing device to identify character strings, associate the character string with an out-of-vocabulary language model score; and determine, based at least in part on a spatial model score associated with the gesture and the out-of-vocabulary language model score, a combined score that indicates a probability that the character string corresponds to the gesture; and output for display the character string.

Gesture keyboard input of non-dictionary character strings using substitute scoring

A data communication system comprises a network management center and switching nodes which are interconnected by regular and spare routes. Each of the regular and spare routes comprises data channels and a control chnanel, the data channels of the regular routes forming a data network for carrying signals to and from user terminals and the control channel of each regular or spare route is connected to the control channels of other regular or spare routes to form a control network of multidrop structure for carrying a network management signal from the center to the nodes as well as network response signals from the nodes to the center. Each of the nodes transmits a request signal through the control network in the event of a line fault in the transmission lines to request permission to establish a new regular route to an adjacent node and transmits a grant signal through the control network in response to receipt of a request signal from an adjacent node indicating that the request is granted if an alternate route is available. The control network is dynamically reconfigured in accordance with the presence and absence of the request signal and the grant signal received from adjacent nodes.

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Tokyo, Japan

Keisuke Kuroyanagi