Abstract: Techniques for providing an arc layout for a soft input panel are described. In some examples, an electronic device can transition from providing a substantially straight and/or horizontal layout for the soft input panel to an arc layout for the soft input panel. The electronic device can display a graphical element at a location on the soft input panel. The electronic device can receive input corresponding to, for example, a swipe of the graphical element in a curved manner across the soft input panel. Based on the input, the electronic device can transition from displaying the soft input panel using the substantially straight layout to displaying the soft input panel using the arc layout.

Abstract: Techniques are provided for customizing a design of a soft input panel. An electronic device can provide a keyboard customization interface to enable a user to specify a color, font, background image, and the like for the soft input panel. The user may provide input through the keyboard customization interface to customize the design (e.g., theme) of the soft input panel. The user may provide an image to be used as a background for the soft input panel. The electronic device can analyze the image to determine a most prominent color of the image. A portion of the soft input panel can be set to a color that is based on the most prominent color of the image.

Abstract: Systems, methods, and computer media for intent-based, dynamic generation and display of task icons within virtual keyboards are provided herein. A system can include a processor, an intent classifier, and a user interface generator. The intent classifier can be configured to determine user intent candidates based on contextual information. A user interface generator can be configured to generate the virtual keyboard for display and, upon receiving an indication of a user intent determined based on the user intent candidates, generate a task icon within the virtual keyboard. The task icon represents functionality associated with the determined user intent. Interaction with the task icon in the virtual keyboard can launch functionality associated with the determined intent. The user interface generator can also be configured to present a search interface upon receiving an indication of a user interaction with the virtual keyboard.

Abstract: An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate.

Abstract: An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate.

Abstract: Systems, methods, and computer media for intent-based, dynamic generation and display of task icons within virtual keyboards are provided herein. A system can include a processor, an intent classifier, and a user interface generator. The intent classifier can be configured to determine user intent candidates based on contextual information. A user interface generator can be configured to generate the virtual keyboard for display and, upon receiving an indication of a user intent determined based on the user intent candidates, generate a task icon within the virtual keyboard. The task icon represents functionality associated with the determined user intent. Interaction with the task icon in the virtual keyboard can launch functionality associated with the determined intent.

Abstract: Systems, methods, and computer media for intent-based, dynamic generation and display of task icons within virtual keyboards are provided herein. A system can include a processor, an intent classifier, and a user interface generator. The intent classifier can be configured to determine user intent candidates based on contextual information. A user interface generator can be configured to generate the virtual keyboard for display and, upon receiving an indication of a user intent determined based on the user intent candidates, generate a task icon within the virtual keyboard. The task icon represents functionality associated with the determined user intent. Interaction with the task icon in the virtual keyboard can launch functionality associated with the determined intent. The user interface generator can also be configured to present a search interface upon receiving an indication of a user interaction with the virtual keyboard.

Abstract: An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate.

Abstract: Techniques for customizing a design of a soft input panel are described herein. For instance, an electronic device can provide a keyboard customization interface to enable a user to specify a color, font, background image, and so on for the soft input panel. The user may provide input through the keyboard customization interface to customize the design (e.g., theme) of the soft input panel. In some instances, the user may provide an image to be used as a background for the soft input panel. The electronic device can analyze the image to determine a most prominent color of the image. A portion of the soft input panel can be set to a color that is based on the most prominent color of the image.

Abstract: Techniques for providing an arc layout for a soft input panel are described. In some examples, an electronic device can transition from providing a substantially straight and/or horizontal layout for the soft input panel to an arc layout for the soft input panel. The electronic device can display a graphical element at a location on the soft input panel. The electronic device can receive input corresponding to, for example, a swipe of the graphical element in a curved manner across the soft input panel. Based on the input, the electronic device can transition from displaying the soft input panel using the substantially straight layout to displaying the soft input panel using the arc layout.

Abstract: An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate.

Abstract: Systems and methods allow an on-line game to extract information relevant to a specific need of a game platform or service platform. The specific need relates to management and use of digital content, and is addressed by designing and playing an on-line collaborative game. The rules of the game intend to solve a specific task dictated by the specific need. Players' responses to the game generate a wealth of information related to a specific task objective, such as ranking, sorting, and evaluating a set of digital content items. To compel participation in a game, players can be rewarded with monetary value rewards. As a game illustration, an image selection game (ISG) that exploits human contextual inference is described in detail. The information extracted from ISG is a list of key-image associations, relevant for the task of image sorting and ranking.

Abstract: An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate.

Abstract: An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate.

Abstract: A “Quality-Based Ad Pricer” prices ads as a function of how users respond to a particular page and/or domain to which they are sent by an online advertisement. User experience is improved by ensuring that advertisements that are more relevant to a user are priced less than an ads which are less relevant to the user. In particular, a quality factor for each ad is determined as a property of the advertiser's site based on measured user behaviors with respect to that site. This quality factor is then used in ranking, selecting, and pricing ads in an automated online auction. Further, while ad aggregators are not excluded from the ad market by the pricing rules of the Quality-Based Ad Pricer, these rules ensure that there is a “level playing field” such that ads of merchants are not excluded by the ads of ad aggregators.

Abstract: An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate.

Abstract: A “Constrained Predictive Interface” uses predictive constraints to improve accuracy in user interfaces such as soft keyboards, pen interfaces, multi-touch interfaces, 3D gesture interfaces, EMG based interfaces, etc. In various embodiments, the Constrained Predictive Interface allows users to take any desired action at any time by taking into account a likelihood of possible user actions in different contexts to determine intended user actions. For example, to enable a virtual keyboard interface, various embodiments of the Constrained Predictive Interface provide key “sweet spots” as predictive constraints that allow the user to select particular keys regardless of any probability associated with the selected or neighboring keys. In further embodiments, the Constrained Predictive Interface provides hit target resizing via various piecewise constant touch models in combination with various predictive constraints.

Abstract: A computer-implemented method of indexing a speech lattice for search of audio corresponding to the speech lattice is provided. The method includes identifying at least two speech recognition hypotheses for a word which have time ranges satisfying a criteria. The method further includes merging the at least two speech recognition hypotheses to generate a merged speech recognition hypothesis for the word.

Abstract: A random walk is performed over a graph, such as an augmented bipartite graph, relating to ownership data with respect to a plurality of users and items owned; the graph can provide social links between the users as well. Items can be recommended to users who do not own the items by randomly walking the graph starting at the user node to which the recommendation will be given. The random walk can step from user to user or from user to item; when an item is reached, the node can be absorbing such that the random walk terminates. The arrived item is recommended to the user. Parameters can also be provided to affect decisions made during the walk about which users to walk to and/or whether to walk to a user or an item.

Abstract: A method and apparatus are provided for training parameters in a hidden conditional random field model for use in speech recognition and phonetic classification. The hidden conditional random field model uses parameterized features that are determined from a segment of speech, and those values are used to identify a phonetic unit for the segment of speech. The parameters are updated after processing of individual training samples.