Abstract:
Disclosed herein are systems, methods, and non-transitory computer-readable storage media for collecting web data in order to create diverse language models. A system configured to practice the method first crawls, such as via a crawler operating on a computing device, a set of documents in a network of interconnected devices according to a visitation policy, wherein the visitation policy is configured to focus on novelty regions for a current language model built from previous crawling cycles by crawling documents whose vocabulary considered likely to fill gaps in the current language model. A language model from a previous cycle can be used to guide the creation of a language model in the following cycle. The novelty regions can include documents with high perplexity values over the current language model.
Abstract:
A system and method disclosed for using and updating a database of template responses for a live agent in response to user communications. The method includes computing an average string distance between each response from a live agent and a template, use to generate the response, modifying the computed average string distance based on a customer satisfaction score associated with each response and selecting a response that minimizes the computed average string distance and maximizes customer satisfaction. Upon receiving a further communication on a certain issue, the system presents a prototype response that has been added to the template database to the live agent for use in generating a response to the further communication that reduces handling time and increases customer satisfaction.
Abstract:
A system, method and computer-readable storage devices are for processing natural language commands, such as commands to a robotic arm, using a Tag & Parse approach to semantic parsing. The system first assigns semantic tags to each word in a sentence and then parses the tag sequence into a semantic tree. The system can use statistical approach for tagging, parsing, and reference resolution. Each stage can produce multiple hypotheses, which are re-ranked using spatial validation. Then the system selects a most likely hypothesis after spatial validation, and generates or outputs a command. In the case of a robotic arm, the command is output in Robot Control Language (RCL).
Abstract:
Information is aggregated and made available to users. A system monitors over the internet a first set of external information sources for a first user based on instructions from a first user profile that specifies information to aggregate for the first user. The system detects, based on the monitoring, new data at one of the first set of information sources. The system obtains the new data at the one of the first set of information sources, independent of preferences of the one of the first set of information sources. The system updates aggregated information for the first user with the new data from the one of the first set of information sources. The updated aggregated information for the first user is made available to the first user.
Abstract:
Systems, methods, and computer-readable storage media relate to performing a search. A system configured to practice the method first receives from an automatic speech recognition (ASR) system a word lattice based on speech query and receives indexed documents from an information repository. The system composes, based on the word lattice and the indexed documents, at least one triple including a query word, selected indexed document, and weight. The system generates an N-best path through the word lattice based on the at least one triple and re-ranks ASR output based on the N-best path. The system aggregates each weight across the query words to generate N-best listings and returns search results to the speech query based on the re-ranked ASR output and the N-best listings. The lattice can be a confusion network, the arc density of which can be adjusted for a desired performance level.
Abstract:
Disclosed are systems, methods, and computer readable media for retrieving digital images. The method embodiment includes converting a descriptive audio stream of a digital video that is provided for the visually impaired to text and then aligning that text to the appropriate segment of the digital video. The system then indexes the converted text from the descriptive audio stream with the text's relationship to the digital video. The system enables queries using action words describing a desired scene from a digital video.
Abstract:
Disclosed herein are systems, computer-implemented methods, and tangible computer-readable media for enriching spoken language translation with dialog acts. The method includes receiving a source speech signal, tagging dialog acts associated with the received source speech signal using a classification model, dialog acts being domain independent descriptions of an intended action a speaker carries out by uttering the source speech signal, producing an enriched hypothesis of the source speech signal incorporating the dialog act tags, and outputting a natural language response of the enriched hypothesis in a target language. Tags can be grouped into sets such as statement, acknowledgement, abandoned, agreement, question, appreciation, and other. The step of producing an enriched translation of the source speech signal uses a dialog act specific translation model containing a phrase translation table.
Abstract:
Disclosed herein are systems, methods, and computer-readable storage media for improving speech recognition accuracy using textual context. The method includes retrieving a recorded utterance, capturing text from a device display associated with the spoken dialog and viewed by one party to the recorded utterance, and identifying words in the captured text that are relevant to the recorded utterance. The method further includes adding the identified words to a dynamic language model, and recognizing the recorded utterance using the dynamic language model. The recorded utterance can be a spoken dialog. A time stamp can be assigned to each identified word. The method can include adding identified words to and/or removing identified words from the dynamic language model based on their respective time stamps. A screen scraper can capture text from the device display associated with the recorded utterance. The device display can contain customer service data.
Abstract:
Disclosed herein are systems, methods, and computer-readable storage media for improving speech recognition accuracy using textual context. The method includes retrieving a recorded utterance, capturing text from a device display associated with the spoken dialog and viewed by one party to the recorded utterance, and identifying words in the captured text that are relevant to the recorded utterance. The method further includes adding the identified words to a dynamic language model, and recognizing the recorded utterance using the dynamic language model. The recorded utterance can be a spoken dialog. A time stamp can be assigned to each identified word. The method can include adding identified words to and/or removing identified words from the dynamic language model based on their respective time stamps. A screen scraper can capture text from the device display associated with the recorded utterance. The device display can contain customer service data.
Abstract:
Disclosed are systems, methods, and computer readable media for retrieving digital images. The method embodiment includes converting a descriptive audio stream of a digital video that is provided for the visually impaired to text and then aligning that text to the appropriate segment of the digital video. The system then indexes the converted text from the descriptive audio stream with the text's relationship to the digital video. The system enables queries using action words describing a desired scene from a digital video.