Abstract: An interactive response system directs input to a software-based router, which is able to intelligently respond to the input by drawing on a combination of human agents, advanced recognition and expert systems. The system utilizes human “intent analysts” for purposes of interpreting customer input. Automated recognition subsystems are trained by coupling customer input with IA-selected intent corresponding to the input, using model-updating subsystems to develop the training information for the automated recognition subsystems.

Abstract: We have invented a process and method for creating a general-purpose adaptive or static machine-learning classifier using prediction by partial matching (PPM) language modeling. This classifier can incorporate homogeneous or heterogeneous feature types; variable-size contexts; sequential or non-sequential features. Features are ordered (linearized) by information saliency; and truncation of least-informative context is used for backoff to handle previously unseen events. Labels may be endogenous (from within the group) or exogenous (outside the group) of the feature types. Classification may generate labels and their probabilities; or only labels. Classification stores may be complete or minimized where redundant states are removed producing significant space savings and performance improvements. Classifiers may be static (unchanging) or online (adaptive or updatable incrementally or in batch). PPM classifiers may be incorporated in ensembles of other PPM classifiers or different machine learning algorithms.

Abstract: We describe here a system and method for creating, maintaining and using a semantic search engine environment for precise retrieval of curated answers to questions where the answers may be drawn from an authoritative document collection. The invention combines processing by human developers and software: semantic editing tools for creating, storing, maintaining queries and variants of queries, and query and document passage categories; links from queries to text passages that provide answers to these queries; a document retrieval store; means for matching user queries against stored queries; means for creating, storing, maintaining, and retrieving semantic and management metadata and categories about queries and documents and using these data for navigating the document collection; and means for finding information related to the user's information need by text and semantic similarity retrieval.

Abstract: An interactive response system directs input to a software-based router, which is able to intelligently respond to the input by drawing on a combination of human agents, advanced recognition and expert systems. The system utilizes human “intent analysts” for purposes of interpreting customer input. Automated recognition subsystems are trained by coupling customer input with IA-selected intent corresponding to the input, using model-updating subsystems to develop the training information for the automated recognition subsystems.

Abstract: An interactive response system directs input to a software-based router, which is able to intelligently respond to the input by drawing on a combination of human agents, advanced recognition and expert systems. The system utilizes human “intent analysts” for purposes of interpreting customer input. Automated recognition subsystems are trained by coupling customer input with IA-selected intent corresponding to the input, using model-updating subsystems to develop the training information for the automated recognition subsystems.

Abstract: An interactive response system mixes HSR subsystems with ASR subsystems to facilitate overall capability of user interfaces. The system permits imperfect ASR subsystems to nonetheless relieve burden on HSR subsystems. An ASR proxy is used to implement an IVR system, and the proxy dynamically selects one or more recognizers from a language model and a human agent to recognize user input. Selection of the one or more recognizers is based on factors such as confidence thresholds of the ASRs and availability of human resources for HSRs.

Abstract: An interactive response system mixes HSR subsystems with ASR subsystems to facilitate overall capability of voice user interfaces. The system permits imperfect ASR subsystems to nonetheless relieve burden on HSR subsystems. An ASR proxy is used to implement an IVR system, and the proxy dynamically determines how many ASR and HSR subsystems are to perform recognition for any particular utterance, based on factors such as confidence thresholds of the ASRs and availability of human resources for HSRs.

Abstract: An interactive response system mixes HSR subsystems with ASR subsystems to facilitate overall capability of voice user interfaces. The system permits imperfect ASR subsystems to nonetheless relieve burden on HSR subsystems. An ASR proxy is used to implement an IVR system, and the proxy dynamically determines how many ASR and HSR subsystems are to perform recognition for any particular utterance, based on factors such as confidence thresholds of the ASRs and availability of human resources for HSRs. In some embodiments, the ASR proxy dynamically selects one or more recognizers based at least in part on the identified grammar and the time length of the utterance.

Abstract: The present invention relates to an apparatus system and method for creating a customizable and application-specific semantic similarity utility that uses a single similarity measuring algorithm with data from broad-coverage structured lexical knowledge bases (dictionaries and thesauri) and corpora (document collections). More specifically the invention includes the use of data from custom or application-specific structured lexical knowledge bases and corpora and semantic mappings from variant expressions to their canonical forms. The invention uses a combination of technologies to simplify the development of a generic semantic similarity utility; and minimize the effort and complexity of customizing the generic utility for a domain- or topic-dependent application. The invention makes customization modular and data-driven, allowing developers to create implementations at varying degrees of customization (e.g., generic, domain-level, company-level, application-level) and also as changes occur over time (e.g.

Abstract: An interactive response system directs input to a software-based router, which is able to intelligently respond to the input by drawing on a combination of human agents, advanced recognition and expert systems. The system utilizes human “intent analysts” for purposes of interpreting customer input. Automated recognition subsystems are trained by coupling customer input with IA-selected intent corresponding to the input, using model-updating subsystems to develop the training information for the automated recognition subsystems.

Abstract: We describe here a system and method for creating, maintaining and using a semantic search engine environment for precise retrieval of curated answers to questions where the answers may be drawn from an authoritative document collection. The invention combines processing by human developers and software: semantic editing tools for creating, storing, maintaining queries and variants of queries, and query and document passage categories; links from queries to text passages that provide answers to these queries; a document retrieval store; means for matching user queries against stored queries; means for creating, storing, maintaining, and retrieving semantic and management metadata and categories about queries and documents and using these data for navigating the document collection; and means for finding information related to the user's information need by text and semantic similarity retrieval.

Abstract: The present invention relates to an apparatus system and method for creating a customizable and application-specific semantic similarity utility that uses a single similarity measuring algorithm with data from broad-coverage structured lexical knowledge bases (dictionaries and thesauri) and corpora (document collections). More specifically the invention includes the use of data from custom or application-specific structured lexical knowledge bases and corpora and semantic mappings from variant expressions to their canonical forms. The invention uses a combination of technologies to simplify the development of a generic semantic similarity utility; and minimize the effort and complexity of customizing the generic utility for a domain- or topic-dependent application. The invention makes customization modular and data-driven, allowing developers to create implementations at varying degrees of customization (e.g., generic, domain-level, company-level, application-level) and also as changes occur over time (e.g.

Abstract: An interactive response system directs input to a software-based router, which is able to intelligently respond to the input by drawing on a combination of human agents, advanced recognition and expert systems. The system utilizes human “intent analysts” for purposes of interpreting customer input. Automated recognition subsystems are trained by coupling customer input with IA-selected intent corresponding to the input, using model-updating subsystems to develop the training information for the automated recognition subsystems.

Abstract: We describe here a system and method for creating, maintaining and using a semantic search engine environment for precise retrieval of curated answers to questions where the answers may be drawn from an authoritative document collection. The invention combines processing by human developers and software: semantic editing tools for creating, storing, maintaining queries and variants of queries, and query and document passage categories; links from queries to text passages that provide answers to these queries; a document retrieval store; means for matching user queries against stored queries; means for creating, storing, maintaining, and retrieving semantic and management metadata and categories about queries and documents and using these data for navigating the document collection; and means for finding information related to the user's information need by text and semantic similarity retrieval.

Abstract: We have invented a process and method for creating a general-purpose adaptive or static machine-learning classifier using prediction by partial matching (PPM) language modeling. This classifier can incorporate homogeneous or heterogeneous feature types; variable-size contexts; sequential or non-sequential features. Features are ordered (linearized) by information saliency; and truncation of least-informative context is used for backoff to handle previously unseen events. Labels may be endogenous (from within the group) or exogenous (outside the group) of the feature types. Classification may generate labels and their probabilities; or only labels. Classification stores may be complete or minimized where redundant states are removed producing significant space savings and performance improvements. Classifiers may be static (unchanging) or online (adaptive or updatable incrementally or in batch). PPM classifiers may be incorporated in ensembles of other PPM classifiers or different machine learning algorithms.

Abstract: An interactive response system mixes HSR subsystems with ASR subsystems to facilitate overall capability of voice user interfaces. The system permits imperfect ASR subsystems to nonetheless relieve burden on HSR subsystems. An ASR proxy is used to implement an IVR system, and the proxy dynamically determines how many ASR and HSR subsystems are to perform recognition for any particular utterance, based on factors such as confidence thresholds of the ASRs and availability of human resources for HSRs.

Abstract: An interactive response system mixes HSR subsystems with ASR subsystems to facilitate overall capability of voice user interfaces. The system permits imperfect ASR subsystems to nonetheless relieve burden on HSR subsystems. An ASR proxy is used to implement an IVR system, and the proxy dynamically determines how many ASR and HSR subsystems are to perform recognition for any particular utterance, based on factors such as confidence thresholds of the ASRs and availability of human resources for HSRs.

Abstract: A computer implemented method for generating a report that includes latent information, comprising receiving an input data stream that includes latent information, performing one of normalization, validation, and extraction of the input data stream, processing the input data stream to identify latent information within the data stream that is required for generation of a particular report, wherein said processing of the input data stream to identify latent information comprises of identifying a relevant portion of the input data stream, bounding the relevant portion of the input data stream, classifying and normalizing the bounded data, activating a relevant report template based on said identified latent information, populating said template with template-specified data, and processing the template-specified data to generate a report.

Abstract: The invention involves the loading and unloading of dynamic section grammars and language models in a speech recognition system. The values of the sections of the structured document are either determined in advance from a collection of documents of the same domain, document type, and speaker; or collected incrementally from documents of the same domain, document type, and speaker; or added incrementally to an already existing set of values. Speech recognition in the context of the given field is constrained to the contents of these dynamic values. If speech recognition fails or produces a poor match within this grammar or section language model, speech recognition against a larger, more general vocabulary that is not constrained to the given section is performed.

Abstract: We describe here a system and method for creating, maintaining and using a semantic search engine environment for precise retrieval of curated answers to questions where the answers may be drawn from an authoritative document collection. The invention combines processing by human developers and software: semantic editing tools for creating, storing, maintaining queries and variants of queries, and query and document passage categories; links from queries to text passages that provide answers to these queries; a document retrieval store; means for matching user queries against stored queries; means for creating, storing, maintaining, and retrieving semantic and management metadata and categories about queries and documents and using these data for navigating the document collection; and means for finding information related to the user's information need by text and semantic similarity retrieval.