Abstract: Techniques are disclosed for adjusting a ranking of information content of a software application based on feedback from a user. One embodiment presented herein includes a method comprising receiving, at a computing device, an audio stream comprising audio of the user, the audio being indicative of feedback related to information content. The method further comprises analyzing the audio stream for paralinguistic information to determine an attribute of the user. The method further comprises adjusting a ranking of the information content based on at least one of the feedback and additional feedback and the determined attribute of the user.

Abstract: Techniques are disclosed for dynamically personalizing application content presented to a user based on “voice-of-customer” feedback, in real-time. As described, the user may provide voice-of-customer feedback characterizing an initial selection of application content presented to the user may be evaluated to identify a set of topics referenced by the voice-of-customer feedback. Keywords associated with the identified topics may be used to enhance the selection of application content presented to the user. For example, keywords associated with the identified topics may be added to an initial search query composed by the user. Doing so can improve the relevance or helpfulness of information content or software interfaces identified using the query.

Abstract: A method and system improves content searching in a question and answer customer support system by using a crowd-machine learning hybrid predictive model, according to one embodiment. The question and answer customer support system determines which customer support content to provide to users by using the hybrid predictive model, according to one embodiment. The question and answer customer support system receives a search query from a user and applies the search query (or a representation of the search query) to the hybrid predictive model, according to one embodiment. The hybrid predictive model generates a likelihood that particular customer support content is relevant to a user's search query, according to one embodiment. The question and answer customer support system acquires user feedback from users and updates/trains the hybrid predictive model based on the user feedback, according to one embodiment.

Abstract: Disclosed methods and systems provide domain-specific incremental search results for search query terms with a customer self-service system for a financial management system, according to one embodiment. Incremental search results are search results that are generated for search query terms, as a user enters the search query terms as part of a search query to a customer self-service system, according to one embodiment. The customer self-service system receives search query terms (e.g., a partial search query) in a search text box, searches customer self-service system content for content that is relevant to the search query terms, and provides incremental search results in a results text box (e.g., drop down menu) that is proximate to (e.g., below) the search text box, according to one embodiment.

Abstract: Embodiments presented herein provide techniques for inferring the current emotional state of a user based on paralinguistic features derived from audio input from that user. If the emotional state meets triggering conditions, the system provides the user with a prompt which allows the user to connect with a support agent. If the user accepts, the system selects a support agent for the user based on the predicted emotional state and on attributes of the support agent found in an agent profile. The system can also determine a priority level for the user based on the score and based on a profile of the user and determine where to place the user in a queue for the support agent.

Abstract: Techniques are disclosed for adjusting a ranking of information content of a software application based on feedback from a user. One embodiment presented herein includes a method comprising receiving, at a computing device, an audio stream comprising audio of the user, the audio being indicative of feedback related to information content. The method further comprises analyzing the audio stream for paralinguistic information to determine an attribute of the user. The method further comprises adjusting a ranking of the information content based on at least one of the feedback and additional feedback and the determined attribute of the user.

Abstract: Embodiments presented herein provide techniques for inferring the current emotional state of a user based on paralinguistic features derived from audio input from that user. If the emotional state meets triggering conditions, the system provides the user with a prompt which allows the user to connect with a support agent. If the user accepts, the system selects a support agent for the user based on the predicted emotional state and on attributes of the support agent found in an agent profile. The system can also determine a priority level for the user based on the score and based on a profile of the user and determine where to place the user in a queue for the support agent.

Abstract: Techniques are disclosed for adjusting user experience of a software application based on paralinguistic information. One embodiment presented herein includes a computer-implemented method for adjusting a user experience of a software application. The method comprises receiving, at a computing device, an audio stream comprising audio of a user. The method further comprises analyzing the audio stream for paralinguistic information to determine an attribute of the user. The method further comprises identifying content of the audio stream. The method further comprises determining one or more actions based on the content of the audio stream. The method further comprises selecting at least one of the one or more actions based on the attribute of the user.

Abstract: Techniques are disclosed for assisting a support agent based on paralinguistic information determined from a user interacting with a software application. One embodiment presented herein includes a computer-implemented method. The method includes receiving, at a computing device, an audio stream including audio of a user interacting with an application. The method also includes evaluating the audio stream to identify a collection of paralinguistic information present in the audio stream. The paralinguistic information includes a set of descriptors characterizing acoustic aspects of the audio that are distinct from verbal content of the audio. The method further includes determining, from the paralinguistic information, attribute measures associated with the user interacting with the application.

Abstract: A method and system provides personalized search results to users of a data management system. The method and system receives a search query from a user and generate initial search results including a plurality of assistance documents relevant to the query data. The method and system utilizes natural language analysis and machine learning processes to analyze the query data, user attributes data, and the assistance documents in order to generate personalized previews of the assistance documents for the user. The method and system output personalized search results to the user including the personalized previews of the assistance documents.

Abstract: A customer self-help system employs artificial intelligence to generate personalized self-help content that is responsive to a user query submitted to the customer self-help system, according to one embodiment. The customer self-help system includes a pre-processor that characterizes and categorizes the self-help content into self-help content components, by using one or more content processing algorithms (e.g., a natural language processing algorithm), according to one embodiment. The customer self-help system includes an intent extractor engine that determines characteristics of the user query based on the user query and user profile data, according to one embodiment. The customer self-help system aggregates portions of the self-help content components into a personalized self-help content by matching characteristics of the user query with characteristics of the self-help content, according to one embodiment.

Abstract: The present disclosure includes techniques for selecting a response to an audio stream query. In one embodiment, an application server receives an audio stream query including content spoken by a user interacting with a voice-user interface. The application server determines a set of paralinguistic features from the audio stream query, and estimates at least a first attribute of the user based on the set of paralinguistic features. The application server identifies subject matter corresponding to the spoken content in the audio stream query, and determines two or more query responses corresponding to the identified subject matter. The application server then selects one of the query responses to present to the user based, at least in part, on the attribute of the user estimated from the set of paralinguistic features.

Abstract: The present disclosure relates to processing support requests, or support queries, in a software application including automated and human interaction-based support systems. An example method generally includes receiving a support request from a client device. A query processor parses the support request to identify one or more characteristics of the support request and identifies a support system to process the support request based at least in part on the identified one or more characteristics of the support request. The query processor instantiates a support session with the identified support system to process the support request.

Abstract: Embodiments presented herein provide techniques for inferring the current emotional state of a user based on paralinguistic features derived from audio input from that user. If the emotional state meets triggering conditions, the system provides the user with a prompt which allows the user to connect with a support agent. If the user accepts, the system selects a support agent for the user based on the predicted emotional state and on attributes of the support agent found in an agent profile. The system can also determine a priority level for the user based on the score and based on a profile of the user and determine where to place the user in a queue for the support agent.

Abstract: Techniques are disclosed for adjusting a ranking of information content of a software application based on feedback from a user. One embodiment presented herein includes a method comprising receiving, at a computing device, an audio stream comprising audio of the user, the audio being indicative of feedback related to information content. The method further comprises analyzing the audio stream for paralinguistic information to determine an attribute of the user. The method further comprises adjusting a ranking of the information content based on at least one of the feedback and additional feedback and the determined attribute of the user.

Abstract: Techniques are disclosed for determining application experience of a user based on paralinguistic information determined for the user. One embodiment presented herein includes a computer-implemented method, which includes receiving, at a computing device, one or more audio streams. Each audio stream includes audio from a user interacting with at least one page of an application. The computer-implemented method also includes generating paralinguistic information from at least one of the audio streams. The paralinguistic information characterizes acoustic aspects of the audio stream that are distinct from verbal content of the audio stream.

Abstract: Techniques are disclosed for adjusting a ranking of information content of a software application based on feedback from a user. One embodiment presented herein includes a method comprising receiving, at a computing device, an audio stream comprising audio of the user, the audio being indicative of feedback related to information content. The method further comprises analyzing the audio stream for paralinguistic information to determine an attribute of the user. The method further comprises adjusting a ranking of the information content based on at least one of the feedback and additional feedback and the determined attribute of the user.

Abstract: Disclosed methods and systems provide domain-specific incremental search results for search query terms with a customer self-service system for a financial management system, according to one embodiment. Incremental search results are search results that are generated for search query terms, as a user enters the search query terms as part of a search query to a customer self-service system, according to one embodiment. The customer self-service system receives search query terms (e.g., a partial search query) in a search text box, searches user content (e.g., business transactions, personal transactions, etc.) and customer self-service system content for content that is relevant to the search query terms, and provides incremental search results navigation links within a results text box to enable users to easily see search results (e.g., transaction records) and to enable users to navigate to transactions records or other user content, from the results text box, according to one embodiment.

Abstract: Disclosed methods and systems provide domain-specific type ahead suggestions for search query terms with a customer self-service system for a tax return preparation system, according to one embodiment. Type ahead suggestions include suggestions for completing a single search query term and/or suggestions for completing a search query having multiple search query terms. The customer self-service system receives one or more search query terms in a search text box, searches for potential search queries that are likely to complete the one or more search query terms, and provides a selected one of the potential search queries in the search text box as a type ahead suggestion, adjacent to the received one or more search query terms, according to one embodiment. The customer self-service system selects one of the potential search queries based on the received search query terms, the user's profile, and/or the user's tax data, according to one embodiment.

Abstract: Disclosed methods and systems provide domain-specific incremental search results for search query terms with a customer self-service system for a financial management system, according to one embodiment. Incremental search results are search results that are generated for search query terms, as a user enters the search query terms as part of a search query to a customer self-service system, according to one embodiment. The customer self-service system receives search query terms (e.g., a partial search query) in a search text box, searches customer self-service system content for content that is relevant to the search query terms, and provides incremental search results in a results text box (e.g., drop down menu) that is proximate to (e.g., below) the search text box, according to one embodiment.