Specialized digital assistants are described that provide scoped natural language, outcome focused options. Techniques and systems for generating the specialists are also provided so that the specialists can be embedded in or employed by other software applications. A specialist can be added directly to a website or application so that visitors to the website or application can more easily interact with the website or application and obtain desired outcomes. More than one specialist may be included in a website or application. The specialist is supported by a back-end specialized digital assistant service (“service platform”) that is scoped to the particular aspects of the website or application. The service platform can provide developer assistance by, upon receiving an indication that a specialized digital assistant component is being included in an application or a webpage, setting up a specialized digital assistant for that component.

According to one embodiment, a speech translation apparatus includes a speech recognition unit, a machine translation unit, an extracting unit, and a receiving unit. The extracting unit extracts words used for a meeting from a word set, based on information related to the meeting, and sends the extracted words to the speech recognition unit and the machine translation unit. The receiving unit receives the speech in a first language in the meeting. The speech recognition unit recognizes the speech in the first language as a text in the first language. The machine translation unit translates the text in the first language into a text in a second language.

Systems and methods that enable usage of a modified Bayesian classification to enable sentiment estimation in social media. In some embodiments, events are classified, and the words described sequentially to the event are processed. The system processes historical information and current information to identify the most likely subclass a document belongs to, to help in the estimation of sentiment of a social media user.

A system and method for speech-to-text translation. The method includes determining, based on at least one audio input in a first language, at least one original language concept; identifying, based on the determined at least one original language concept, the first language of the at least one audio input; determining, for each original language concept, a matching translated concept, wherein each matching translated concept is associated with a second language, wherein the second language is different from the first language; generating a textual output based on the determined at least one translated concept.

A language learning system that teaches an individualized set of vocabulary words to users through an interactive story. The interactive story is modeled through probabilistic rules in a semantic network having objects and relations. Dialog and narration is generated dynamically based on the state of the interactive story model using phrasal rewrite rules evaluated with a four-valued logic system in which truth values of the objects and relations are encoded as true, false, defined, and undefined in parallel memory structures.

Methods, systems, and computer program products for consolidating Web pages displayed in multiple browsers at a computer processing device are provided. A method includes generating an information file in response to initiation of a browser instance and creating a file record for each web page accessed during the browser instance. The file record includes session history data for each web page. The method also includes consolidating each of the file records from the information file with other file records from another information file created in response to another browser instance. The method further includes displaying a single view of browser activity corresponding to the browser instance and the other browser instance resulting from the consolidation.

A system for providing an internet fax service has an engine to process a raw fax document, received for a user of the internet fax service, using digital character recognition to produce recognized text or an associated formatted text document. A conversion engine may convert the raw fax to native file format being one of a) word processor format, b) spreadsheet format, c) slide presentation format, or d) another format that can be read on a user interface. An internet server is to make the native file format document available to the user over an internet. A fax content processing unit is to perform keyword scanning of the recognized text, and then allows the user to search for stored faxes by keyword. Other embodiments are also described.

Disclosed herein are systems, computer-implemented methods, and tangible computer-readable storage media for generating a natural language spoken dialog system. The method includes nominating a set of allowed dialog actions and a set of contextual features at each turn in a dialog, and selecting an optimal action from the set of nominated allowed dialog actions using a machine learning algorithm. The method includes generating a response based on the selected optimal action at each turn in the dialog. The set of manually nominated allowed dialog actions can incorporate a set of business rules. Prompt wordings in the generated natural language spoken dialog system can be tailored to a current context while following the set of business rules. A compression label can represent at least one of the manually nominated allowed dialog actions.

Embodiments relate to a method, apparatus and program product and for generating a natural language processing model for an information domain. The method derives a skeleton of a natural language lexicon from a source model and uses it to form a dictionary. It also applies a set of syntactical rules defining concepts and relationships to the dictionary and expands the skeleton of the natural language lexicon based on a plurality of reference documents from the information domain. Using the expanded skeleton of the natural language lexicon, it also provides a natural language processing model for the information domain.

A computer-implemented method, program product, and system, for extracting pieces of text from a plurality of pieces of text. The method includes: primarily evaluating a measure of positive expressions and a measure of negative expressions included in each of pieces of text; secondarily evaluating each of the pieces of text on the basis of a plurality of evaluation functions, where certain evaluation functions among the plurality of evaluation functions include, as variables, the measure of positive expressions and the measure of negative expressions; and extracting a piece of text having an evaluation result with a higher rating in preference to a piece of text having an evaluation result with a lower rating, where the individual evaluation results are based on the same evaluation function among the plurality of evaluation functions.