Abstract: Described are natural language web browsers configured to provide a natural language interface to an existing web browser or a newly created web browser. That is, users interact with the web browser employing speech (or text) as input and output instead of using a mouse and keyboard as input and an electronic display screen as output. Embodiments of a natural language web browser converts user questions, statements, and/or commands into actions, reads the resulting HTML and converts the HTML into natural language descriptions to provide to the user.

Abstract: Described are natural language web browsers configured to provide a natural language interface to an existing web browser or a newly created web browser. That is, users interact with the web browser employing speech (or text) as input and output instead of using a mouse and keyboard as input and an electronic display screen as output. Embodiments of a natural language web browser converts user questions, statements, and/or commands into actions, reads the resulting HTML and converts the HTML into natural language descriptions to provide to the user.

Abstract: A system is provided to receive a request for insights based on reviews for a product, wherein the request includes information input by a user relating to configuration information, calibration information, and desired feature information, and wherein the configuration information includes a relevance weight for at least one of a plurality of attributes for each review. The system assigns, based on the relevance weight, a normalized relevance weight for each review. The system generates, by a trained model based on the user-input information and the normalized relevance weight, quantitative and qualitative insights for the reviews. The system displays the quantitative and qualitative insights. The system modifies, by the user, a rating of a displayed qualitative insight term. The system executes the trained model based on the modified rating, and generates and displays updated quantitative and qualitative insights for the reviews.

Abstract: Embodiments described herein provide a system for generating a draft proposal. During operation, the system obtains a schema that represents a general model of a request for proposal (RFP). The system generates a structured RFP from an RFP document by structuring one or more elements of the RFP document in the structured RFP based on the schema. The system then generates a proposal outline comprising one or more sections. A respective one of the one or more sections corresponds to one of the one or more elements. The system obtains a piece of content for a respective section of the one or more sections based on a requirement specified in an element corresponding to the section and inserts the piece of content in the section of the proposal outline.

Abstract: Embodiments of the present invention provide a system for automatically extracting conversational structure from a voice record based on lexical and acoustic features. The system also aggregates business-relevant statistics and entities from a collection of spoken conversations. The system may infer a coarse-level conversational structure based on fine-level activities identified from extracted acoustic features. The system improves significantly over previous systems by extracting structure based on lexical and acoustic features. This enables extracting conversational structure on a larger scale and finer level of detail than previous systems, and can feed an analytics and business intelligence platform, e.g. for customer service phone calls. During operation, the system obtains a voice record. The system then extracts a lexical feature using automatic speech recognition (ASR). The system extracts an acoustic feature.

Abstract: Embodiments described herein provide a system for generating a draft proposal. During operation, the system obtains a schema that represents a general model of a request for proposal (RFP). The system generates a structured RFP from an RFP document by structuring one or more elements of the RFP document in the structured RFP based on the schema. The system then generates a proposal outline comprising one or more sections. A respective one of the one or more sections corresponds to one of the one or more elements. The system obtains a piece of content for a respective section of the one or more sections based on a requirement specified in an element corresponding to the section and inserts the piece of content in the section of the proposal outline.

Abstract: Embodiments of the present invention provide a system for automatically extracting conversational structure from a voice record based on lexical and acoustic features. The system also aggregates business-relevant statistics and entities from a collection of spoken conversations. The system may infer a coarse-level conversational structure based on fine-level activities identified from extracted acoustic features. The system improves significantly over previous systems by extracting structure based on lexical and acoustic features. This enables extracting conversational structure on a larger scale and finer level of detail than previous systems, and can feed an analytics and business intelligence platform, e.g. for customer service phone calls. During operation, the system obtains a voice record. The system then extracts a lexical feature using automatic speech recognition (ASR). The system extracts an acoustic feature.

Abstract: One embodiment of the present invention provides a system for providing assistance to a user of a product in diagnosing faults in the product. During operation, the system receives, at a help server, data associated with current and/or past operation of the product; performs an optimization to determine a sequence of diagnostic actions that is expected to maximize a net benefit to the user. The sequence of diagnostic actions includes one or more actions that require the user to perform at least one task, and performing the optimization involves accounting for costs to the user for performing the at least one task and savings to the user for correcting the faults. The system then interacts with the user, which involves presenting the sequence of diagnostic actions to the user.

Abstract: Described are natural language web browsers configured to provide a natural language interface to an existing web browser or a newly created web browser. That is, users interact with the web browser employing speech (or text) as input and output instead of using a mouse and keyboard as input and an electronic display screen as output. Embodiments of a natural language web browser converts user questions, statements, and/or commands into actions, reads the resulting HTML and converts the HTML into natural language descriptions to provide to the user.

Abstract: Interacting with the driver based on the driver's context can keep help keep the driver alert. The context can be determined determining driver characteristics including the interests and by monitoring the circumstances surrounding the driver, such as the state of the driver using sensors included in the vehicle, the state of the vehicle, and the information about the driver's current locale. The characteristics and the monitored circumstances define the context of driver. Information of interest to the driver is obtained and is used to generate actions that are recommendable to the driver based on the driver's context. The actions are used to keep the driver alert.

Abstract: One embodiment of the present invention provides a system for providing assistance to a user of a product in diagnosing faults in the product. During operation, the system receives, at a help server, data associated with current and/or past operation of the product; performs an optimization to determine a sequence of diagnostic actions that is expected to maximize a net benefit to the user. The sequence of diagnostic actions includes one or more actions that require the user to perform at least one task, and performing the optimization involves accounting for costs to the user for performing the at least one task and savings to the user for correcting the faults. The system then interacts with the user, which involves presenting the sequence of diagnostic actions to the user.