A system and method for adapting a speech recognition and generation system. The system and method include providing a speech recognition and generation engine that processes speech received from a user and providing a dictionary adaptation module that adds out of vocabulary words to a baseline dictionary of the speech recognition and generation system. Words are added by extracting words that are encountered and adding out of vocabulary words to the baseline dictionary of the speech recognition and generation system.

There is provided an information processing apparatus for automatically generating information representing a context surrounding a user, the information processing apparatus including: a recognition processing unit configured to perform, on the basis of user environment information including at feast any of location information representing a location where a user is present, image information relating to an environment surrounding a user, and audio information relating to the environment, an analysis process of at least any of the location information, the image information, and the audio information included in the user environment information, at a predetermined time interval, and to recognize a context surrounding the user, using the acquired result of analysis relating to the user environment; and a context candidate information generating unit configured to generate context candidate information representing a candidate of the context surrounding the user, the context candidate information including, at least, information representing the context surrounding the user and information representing the user's emotion in the context using the result of context recognition performed by the recognition processing unit.

There is provided an information processing apparatus for automatically generating information representing a context surrounding a user, the information processing apparatus including: a recognition processing unit configured to perform, on the basis of user environment information including at feast any of location information representing a location where a user is present, image information relating to an environment surrounding a user, and audio information relating to the environment, an analysis process of at least any of the location information, the image information, and the audio information included in the user environment information, at a predetermined time interval, and to recognize a context surrounding the user, using the acquired result of analysis relating to the user environment; and a context candidate information generating unit configured to generate context candidate information representing a candidate of the context surrounding the user, the context candidate information including, at least, information representing the context surrounding the user and information representing the user's emotion in the context using the result of context recognition performed by the recognition processing unit.

Embodiments of the present invention disclose a method, computer program product, and system for generating a plan for document processing. A plurality of electronic documents are received, by a computer, using a network. The plurality of electronic documents are analyzed, using the computer, to identify a plurality of tabular data, based on the analyzed plurality of electronic documents. Textual data is identified within the identified tabular data, of the analyzed plurality of electronic documents. Textual hints are generated, based on the identified textual data within the identified tabular data. References are identified, wherein references are based on matching textual hints with textual data in the received plurality of electronic documents. A count of references is calculated, associated with one or more sets of tabular data. A priority score is calculated based on the count of references, and an ingestion plan is generated, based on the calculated priority score.

A method for suggesting revisions to a document-under-analysis from a seed database, the seed database including a plurality of original texts each respectively associated with one of a plurality of final texts, the method for suggesting revisions including selecting a statement-under-analysis (“SUA”), selecting a first original text of the plurality of original texts, determining a first edit-type classification of the first original text with respect to its associated final text, generating a first similarity score for the first original text based on the first edit-type classification, the first similarity score representing a degree of similarity between the SUA and the first original text, selecting a second original text of the plurality of original texts, determining a second edit-type classification of the second original text with respect to its associated final text, generating a second similarity score for the second original text based on the second edit-type classification, the second similarity score representing a degree of similarity between the SUA and the second original text, selecting a candidate original text from one of the first original text and the second original text, and creating an edited SUA (“ESUA”) by modifying a copy of the first SUA consistent with a first candidate final text associated with the first candidate original text.

The present invention provides a system and method for optimizing a message. Components of a starting message are identified, and at least one rule is applied for modifying at least one message component to create at least one variation of the starting message. Message variants are tested by sending each variant to a sample of people and measuring a response rate for each sent message variant. The measured response rates are used to create an optimal version of the message. In one embodiment, message variants may be created and tested in multiple rounds.

In accordance with an example embodiment, large scale category classification based on sequence semantic embedding and parallel learning is described. In one example, one or more closest matches are identified by comparison between (i) a publication semantic vector that corresponds to at least part of the publication, the publication semantic vector based on a first machine-learned model that projects the at least part of the publication into a semantic vector space, and (ii) a plurality of category vectors corresponding to respective categories from a plurality of categories.

Source data statements that had been received for the request are semantically analyzed, which includes matching elements in the received source data statements to respective one or more entries in an ontology associated with a domain that had been selected for the received source data statements. The ontology includes items and relationships that define the selected domain. Each element in the received source data statements is a word or a phrase. The one or more entries are assigned to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries. The annotated elements are saved with the respective annotations. The annotations are used to generate a search query for the request.

Systems and methods are provided for creating a cinematic storytelling experience. A user a user selection of a story is received from a client device. User input to initiate verbal recitation of the selected story is received. Correspondence between the verbal recitation and at least one keyword is detected, and the at least one corresponding action is performed.

A first food ingredient may be received. The first food ingredient may comprise a first plurality of chemical constituents. A plurality of candidate food ingredient substitutes may be received. Each candidate food ingredient substitute may comprise a second plurality of chemical constituents. For each of the plurality of candidate food ingredient substitutes, a quantity of the second plurality of chemical constituents that match the first plurality of chemical constituents may be determined. One or more food ingredient substitutes may be identified based on at least the quantity of the second plurality of chemical constituents that match the first plurality of chemical constituents.