Abstract: Real-time query expansion (RTQE) is a process of supplementing an original query with additional terms or expansion choices that are ranked according to some figure of merit and presented while users are still formulating their queries. Individual terms may be combined and submitted as a phrase into a query. By building the phase term-by-term, users can compositionally formulate queries while maintaining the same benefits that other RTQE interfaces offer. The benefits include, reducing the number of keystrokes and improving retrieval performance. To promote greater flexibility in its working environment, the number of terms that are presented on a display may be reduced. In place of some terms, placeholders may be used and expanded by the user when necessary. This allows phrases to be readily presented on small displays (e.g., hand-held devices).

Abstract: This patent application pertains to computing scenarios that allow users to more readily accomplish desired tasks. One implementation includes at least one dictionary of potential auto-suggestions that can be generated in relation to user-input. The implementation also includes a text framework configured to weight at least some of the potential auto-suggestions based upon one or more parameters. This implementation further includes a task engine configured to associate tasks with at least some of the potential auto-suggestions.

Abstract: An apparatus for communicating with a handheld device (e.g., a cellular telephone) is provided herein. A protective shroud is configured to enclose the handheld device and protect it against incidents that commonly cause damage to handheld devices. Integral to the protective shroud is at least one of an input component configured to receive user input and a wireless transceiver configured to transmit signals to and/or receive signals from the handheld device. In one example, where both the input component and the wireless transceiver are integral to the protective shroud, signals related to received user input (e.g., where the shroud serves as a keypad) may be transmitted to the handheld device even if the protective shroud is removed from the handheld device.

Abstract: An architecture is presented that leverages discrepancies between user model predictions and speech recognition results by identifying discrepancies between the predictive data and the speech recognition data and repairing the data based in part on the discrepancy. User model predictions predict what goal or action speech application users are likely to pursue based in part on past user behavior. Speech recognition results indicate what goal speech application users are likely to have spoken based in part on words spoken under specific constraints. Discrepancies between the predictive data and the speech recognition data are identified and a dialog repair is engaged for repairing these discrepancies. By engaging in repairs when there is a discrepancy between the predictive results and the speech recognition results, and utilizing feedback obtained via interaction with a user, the architecture can learn about the reliability of both user model predictions and speech recognition results for future processing.

Abstract: An apparatus for communicating with a handheld device (e.g., a cellular telephone) is provided herein. A protective shroud is configured to enclose the handheld device and protect it against incidents that commonly cause damage to handheld devices. Integral to the protective shroud is at least one of an input component configured to receive user input and a wireless transceiver configured to transmit signals to and/or receive signals from the handheld device. In one example, where both the input component and the wireless transceiver are integral to the protective shroud, signals related to received user input (e.g., where the shroud serves as a keypad) may be transmitted to the handheld device even if the protective shroud is removed from the handheld device.

Abstract: A generic predictive argument model that can be applied to a set of shot values to predict a target slot value is provided. The generic predictive argument model can predict whether or not a particular value or item is the intended target of the user command given various features. A prediction for each of the slot values can then be normalized to infer a distribution over all values or items. For any set of slot values (e.g., contacts), a number of binary variable s are created that indicate whether or not each specific slot value was the intended target. For each slot value, a set of input features can be employed to predict the corresponding binary variable. These input features are generic properties of the contact that are “instantiated” based o n properties of the contact (e.g., contact-specific features). These contact-specific features can be stored in a user data store.

Abstract: An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve the text entry user experience and performance through the use of indicators such as feedback semaphores. Also disclosed are suggestion candidates, which allow a user to quickly select next words to add to text input data, or replacement words for words that have been designated as incorrect. According to one embodiment, a method comprises receiving text input data, providing an indicator for possible correction of the text input data, displaying suggestion candidates associated with alternative words for the data, receiving a single touch screen input selecting one of the suggestion candidates, and modifying the input data using the word associated 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: Apparatus and methods are disclosed for providing feedback and guidance to touch screen device users to improve the text entry user experience and performance. According to one embodiment, a method comprises receiving a text entry, receiving input on a touch screen in the form of a first single touch input located over a word of previously entered text, and presenting the user with one or more suggestion candidates indicated possible replacement words related to the selected word. The user can then select one of the suggestion candidates using a second single touch input to replace the selected word with a word associated with the selected suggestion candidate.

Abstract: This patent application pertains to computing scenarios that allow users to more readily accomplish desired tasks. One implementation includes at least one dictionary of potential auto-suggestions that can be generated in relation to user-input. The implementation also includes a text framework configured to weight at least some of the potential auto-suggestions based upon one or more parameters. This implementation further includes a task engine configured to associate tasks with at least some of the potential auto-suggestions.

Abstract: A dialog system training environment and method using text-to-speech (TTS) are provided. The only knowledge a designer requires is a simple specification of when the dialog system has failed or succeeded, and for any state of the dialog, a list of the possible actions the system can take. The training environment simulates a user using TTS varied at adjustable levels, a dialog action model of a dialog system responds to the produced utterance by trying out all possible actions until it has failed or succeeded. From the data accumulated in the training environment it is possible for the dialog action model to learn which states to go to when it observes the appropriate speech and dialog features so as to increase the likelihood of success. The data can also be used to improve the speech model.

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: An apparatus for communicating with a handheld device (e.g., a cellular telephone) is provided herein. A protective shroud is configured to enclose the handheld device and protect it against incidents that commonly cause damage to handheld devices. Integral to the protective shroud is at least one of an input component configured to receive user input and a wireless transceiver configured to transmit signals to and/or receive signals from the handheld device. In one example, where both the input component and the wireless transceiver are integral to the protective shroud, signals related to received user input (e.g., where the shroud serves as a keypad) may be transmitted to the handheld device even if the protective shroud is removed from the handheld device.

Abstract: A system and method for prediction of a user goal for command/control of a personal device (e.g., mobile phone) is provided. The system employs statistical model(s) that can predict a command based, at least in part, on past user behavior (e.g., probability distribution over a set of predicates, and, optionally arguments). Further, the system can be employed with a speech recognition component to facilitate language modeling for predicting the user goal. The system can include predictive user models (e.g., predicate model and argument model) that receive a user input (e.g., utterance) and employ statistical modeling to determine the likely command without regard to the actual content of the input (e.g., utterance). The system employs features for predicting the next user goal which can be stored in a user data store. Features can capture personal idiosyncrasies or systematic patterns of usage (e.g., device-related, time-related, predicate-related, contact-specific and/or periodic features).

Abstract: An online dialog system and method are provided. The dialog system receives speech input and outputs an action according to its models. After executing the action, the system receives feedback from the environment or user. The system immediately utilizes the feedback to update its models in an online fashion.

Abstract: A system and method for online reinforcement learning is provided. In particular, a method for performing the explore-vs.-exploit tradeoff is provided. Although the method is heuristic, it can be applied in a principled manner while simultaneously learning the parameters and/or structure of the model (e.g., Bayesian network model). The system includes a model which receives an input (e.g., from a user) and provides a probability distribution associated with uncertainty regarding parameters of the model to a decision engine. The decision engine can determine whether to exploit the information known to it or to explore to obtain additional information based, at least in part, upon the explore-vs.-exploit tradeoff (e.g., Thompson strategy). A reinforcement learning component can obtain additional information (e.g., feedback from a user) and update parameter(s) and/or the structure of the model.

Abstract: Architecture for integrating and generating back-off grammars (BOG) in a speech recognition application for recognizing out-of-grammar (OOG) utterances and updating the context-free grammars (CFG) with the results. A parsing component identifies keywords and/or slots from user utterances and a grammar generation component adds filler tags before and/or after the keywords and slots to create new grammar rules. The BOG can be generated from these new grammar rules and can be used to process the OOG user utterances. By processing the OOG user utterances through the BOG, the architecture can recognize and perform the intended task on behalf of the user.

Abstract: Real-time query expansion (RTQE) is a process of supplementing an original query with additional terms or expansion choices that are ranked according to some figure of merit and presented while users are still formulating their queries. As disclosed herein, individual terms may be combined and submitted as a phrase into a query. By building the phase term-by-term, users can compositionally formulate queries while maintaining the same benefits that other RTQE interfaces offer. To promote greater flexibility in its working environment, the number of terms that are presented on a display may be reduced. In place of some terms, placeholders may be used and expanded by the user when necessary. This allows phrases to be readily presented on small displays (e.g., hand-held devices).

Abstract: Real-time query expansion (RTQE) is a process of supplementing an original query with additional terms or expansion choices that are ranked according to some figure of merit and presented while users are still formulating their queries. As disclosed herein, individual terms may be combined and submitted as a phrase into a query. By building the phase term-by-term, users can compositionally formulate queries while maintaining the same benefits that other RTQE interfaces offer. The benefits include, reducing the number of keystrokes and improving retrieval performance. To promote greater flexibility in its working environment, the number of terms that are presented on a display may be reduced. In place of some terms, placeholders may be used and expanded by the user when necessary. This allows phrases to be readily presented on small displays (e.g., hand-held devices).

Abstract: A system for displaying information to a user is disclosed. The system comprises a grouping module that organizes data items into groups that are ranked based upon at least one attribute of the data items. Also included is a presentation module that presents the ranked groups of data items to a user along with a group indicator. Methods for using the disclosed system are additionally provided.