Abstract: Identification of an intent of a conversation can be useful for real-time or post-processing purposes. According to example embodiments, a method, and corresponding apparatus of identifying at least one intent-bearing utterance in a conversation, comprises determining at least one feature for each utterance among a subset of utterances of the conversation; classifying each utterance among the subset of utterances, using a classifier, as an intent classification or a non-intent classification based at least in part on a subset of the at least one determined feature; and selecting at least one utterance, with intent classification, as an intent-bearing utterance based at least in part on classification results by the classifier. Through identification of an intent bearing utterance, a call center for example, can provide improved service for callers through, for example, more effective directing of a call to a live agent.

Abstract: Electrical usage of devices in a building may be monitored to provide information about the operation of the devices to a user. The information communicated to a user may include historical information that is retrieved from a server and real-time information that is received from a power monitoring device. The historical information may be transmitted to the user device over a first network connection where the historical information is retrieved using an identifier received from the user device. The real-time information may be received from a power monitoring device and transmitted to the user device over a second network connection.

Abstract: Selecting a grammar for use in a machine question-answering system, such as a Natural Language Understanding System, can be difficult for non-experts in such grammars. A tool, according to an example embodiment, can compare annotations of sample sentences, performed correctly by a human, the annotations having intents and mentions, against annotations performed by multiple grammars. Each grammar can be scored, and the system can select the best scored grammar for the user. In one embodiment, a method of selecting a grammar includes comparing manually-generated annotations against machine-generated annotations as a function of a given grammar among multiple grammars. The method can further include applying scores to the machine-generated annotations that are a function of weightings of the intents and mentions. The method can additionally include recommending whether to employ the given grammar based on the scores.

Abstract: Designing a natural language understanding (NLU) model for an application from scratch can be difficult for non-experts. A system can simplify the design process by providing an interface allowing a designer to input example usage sentences and build an NLU model based on presented matches to those example sentences. In one embodiment, a method for initializing a workspace for building an NLU system includes parsing a sample sentence to select at least one candidate stub grammar from among multiple candidate stub grammars. The method can include presenting, to a user, respective representations of the candidate stub grammars selected by the parsing of the sample sentence. The method can include enabling the user to choose one of the respective representations of the candidate stub grammars. The method can include adding to the workspace a stub grammar corresponding to the representation of the candidate stub grammar chosen by the user.

Abstract: Electrical usage of devices in a building may be monitored to provide information about the operation of the devices to a user. The information communicated to a user may include historical information and real-time information. In determining the real-time information, it may be desired to provide the information quickly and use a smaller set of features that are available more quickly. In determining the historical information, it may be desired to provide more accurate information and use a larger set of features. A device may compute real-time information and historical information using different sets of features.

Abstract: Electrical usage of devices in a building may be monitored to provide information about the operation of the devices to a user. The information communicated to a user may include historical information that is retrieved from a server and real-time information that is received from a power monitoring device. The historical information may be transmitted to the user device over a first network connection where the historical information is retrieved using an identifier received from the user device. The real-time information may be received from a power monitoring device and transmitted to the user device over a second network connection.

Abstract: Electrical usage of devices in a building may be monitored to provide information about the operation of the devices to a user. The information communicated to a user may include historical information and real-time information. In determining the real-time information, it may be desired to provide the information quickly and use a smaller set of features that are available more quickly. In determining the historical information, it may be desired to provide more accurate information and use a larger set of features. A device may compute real-time information and historical information using different sets of features.

Abstract: A system and method for providing an easy-to-use interface for verifying semantic tags in a steering application in order to generate a natural language grammar. The method includes obtaining user responses to open-ended steering questions, automatically grouping the user responses into groups based on their semantic meaning, and automatically assigning preliminary semantic tags to each of the groups. The user interface enables the user to validate the content of the groups to ensure that all responses within a group have the same semantic meaning and to add or edit semantic tags associated with the groups. The system and method may be applied to interactive voice response (IVR) systems, as well as customer service systems that can communicate with a user via a text or written interface.

Abstract: Methods and systems for setting selected automatic speech recognition parameters are described. A data set associated with operation of a speech recognition application is defined and includes: i. recognition states characterizing the semantic progression of a user interaction with the speech recognition application, and ii. recognition outcomes associated with each recognition state. For a selected user interaction with the speech recognition application, an application cost function is defined that characterizes an estimated cost of the user interaction for each recognition outcome. For one or more system performance parameters indirectly related to the user interaction, the parameters are set to values which optimize the cost of the user interaction over the recognition states.

Abstract: Electrical usage of devices in a building may be monitored to provide information about the operation of the devices to a user. The information communicated to a user may include historical information that is retrieved from a server and real-time information that is received from a power monitoring device. The historical information may be transmitted to the user device over a first network connection where the historical information is retrieved using an identifier received from the user device. The real-time information may be received from a power monitoring device and transmitted to the user device over a second network connection.

Abstract: Labeling a call, for instance by identifying an intent (i.e., the reason why the caller has called into the call center), of a caller in a conversation between a caller and an agent is a useful task for efficient customer relationship management (CRM). In an embodiment, a method of labeling sentences for presentation to a human can include selecting an intent bearing excerpt from sentences, presenting the intent bearing excerpt to the human, and enabling the human to apply a label to each sentence based on the presentation of the intent bearing excerpt. The method can reduce a manual labeling budget while increasing the accuracy of labeling models based on manual labeling.

Abstract: Electrical usage of devices in a building may be monitored to provide information about the operation of the devices to a user. The information communicated to a user may include historical information and real-time information. In determining the real-time information, it may be desired to provide the information quickly and use a smaller set of features that are available more quickly. In determining the historical information, it may be desired to provide more accurate information and use a larger set of features. A device may compute real-time information and historical information using different sets of features.

Abstract: A system and method for providing an easy-to-use interface for verifying semantic tags in a steering application in order to generate a natural language grammar. The method includes obtaining user responses to open-ended steering questions, automatically grouping the user responses into groups based on their semantic meaning, and automatically assigning preliminary semantic tags to each of the groups. The user interface enables the user to validate the content of the groups to ensure that all responses within a group have the same semantic meaning and to add or edit semantic tags associated with the groups. The system and method may be applied to interactive voice response (IVR) systems, as well as customer service systems that can communicate with a user via a text or written interface.

Abstract: Designing a natural language understanding (NLU) model for an application from scratch can be difficult for non-experts. A system can simplify the design process by providing an interface allowing a designer to input example usage sentences and build an NLU model based on presented matches to those example sentences. In one embodiment, a method for initializing a workspace for building an NLU system includes parsing a sample sentence to select at least one candidate stub grammar from among multiple candidate stub grammars. The method can include presenting, to a user, respective representations of the candidate stub grammars selected by the parsing of the sample sentence. The method can include enabling the user to choose one of the respective representations of the candidate stub grammars. The method can include adding to the workspace a stub grammar corresponding to the representation of the candidate stub grammar chosen by the user.

Abstract: Selecting a grammar for use in a machine question-answering system, such as a Natural Language Understanding System, can be difficult for non-experts in such grammars. A tool, according to an example embodiment, can compare annotations of sample sentences, performed correctly by a human, the annotations having intents and mentions, against annotations performed by multiple grammars. Each grammar can be scored, and the system can select the best scored grammar for the user. In one embodiment, a method of selecting a grammar includes comparing manually-generated annotations against machine-generated annotations as a function of a given grammar among multiple grammars. The method can further include applying scores to the machine-generated annotations that are a function of weightings of the intents and mentions. The method can additionally include recommending whether to employ the given grammar based on the scores.

Abstract: A system and method for providing an easy-to-use interface for verifying semantic tags in a steering application in order to generate a natural language grammar. The method includes obtaining user responses to open-ended steering questions, automatically grouping the user responses into groups based on their semantic meaning, and automatically assigning preliminary semantic tags to each of the groups. The user interface enables the user to validate the content of the groups to ensure that all responses within a group have the same semantic meaning and to add or edit semantic tags associated with the groups. The system and method may be applied to interactive voice response (IVR) systems, as well as customer service systems that can communicate with a user via a text or written interface.

Abstract: Identification of an intent of a conversation can be useful for real-time or post-processing purposes. According to example embodiments, a method, and corresponding apparatus of identifying at least one intent-bearing utterance in a conversation, comprises determining at least one feature for each utterance among a subset of utterances of the conversation; classifying each utterance among the subset of utterances, using a classifier, as an intent classification or a non-intent classification based at least in part on a subset of the at least one determined feature; and selecting at least one utterance, with intent classification, as an intent-bearing utterance based at least in part on classification results by the classifier. Through identification of an intent bearing utterance, a call center for example, can provide improved service for callers through, for example, more effective directing of a call to a live agent.

Abstract: Systems, methods, and media for presenting an advertisement are provided. In some embodiments, systems for presenting an advertisement are provided, the systems comprising: at least one hardware processor that: receives information relating to an advertisement space; determines at least one score for each of a plurality of segments for a potential advertisement for the advertisement space; selects a segment from the plurality of segments for the advertisement space based on the at least one score for the plurality of segments; selects an advertisement for the segment selected; and causes the advertisement to be presented in the advertisement space.

Abstract: An interactive user interface is described for setting confidence score thresholds in a language processing system. There is a display of a first system confidence score curve characterizing system recognition performance associated with a high confidence threshold, a first user control for adjusting the high confidence threshold and an associated visual display highlighting a point on the first system confidence score curve representing the selected high confidence threshold, a display of a second system confidence score curve characterizing system recognition performance associated with a low confidence threshold, and a second user control for adjusting the low confidence threshold and an associated visual display highlighting a point on the second system confidence score curve representing the selected low confidence threshold. The operation of the second user control is constrained to require that the low confidence threshold must be less than or equal to the high confidence threshold.

Abstract: Methods and systems for setting selected automatic speech recognition parameters are described. A data set associated with operation of a speech recognition application is defined and includes: i. recognition states characterizing the semantic progression of a user interaction with the speech recognition application, and ii. recognition outcomes associated with each recognition state. For a selected user interaction with the speech recognition application, an application cost function is defined that characterizes an estimated cost of the user interaction for each recognition outcome. For one or more system performance parameters indirectly related to the user interaction, the parameters are set to values which optimize the cost of the user interaction over the recognition states.