Recordset

Abstract: A real-time system incorporating speech recognition and linguistic processing for recognizing a spoken query by a user and distributed between client and server, is disclosed. The system accepts user's queries in the form of speech at the client where minimal processing extracts a sufficient number of acoustic speech vectors representing the utterance. These vectors are sent via a communications channel to the server where additional acoustic vectors are derived. Using Hidden Markov Models (HMMs), and appropriate grammars and dictionaries conditioned by the selections made by the user, the speech representing the user's query is fully decoded into text (or some other suitable form) at the server. This text corresponding to the user's query is then simultaneously sent to a natural language engine and a database processor where optimized SQL statements are constructed for a full-text search from a database for a recordset of several stored questions that best matches the user's query. Further processing in the natural language engine narrows the search to a single stored question. The answer corresponding to this single stored question is next retrieved from the file path and sent to the client in compressed form. At the client, the answer to the user's query is articulated to the user using a text-to-speech engine in his or her native natural language. The system requires no training and can operate in several natural languages.

Abstract: A real-time speech-based learning/training system distributed between client and server, and incorporating speech recognition and linguistic processing for recognizing a spoken question and to provide an answer to the student in a learning or training environment implemented on an intranet or over the Internet, is disclosed. The system accepts the student's question in the form of speech at his or her computer, PDA or workstation where minimal processing extracts a sufficient number of acoustic speech vectors representing the utterance. The system as implemented accepts environmental variables such as course, chapter, section as selected by the user so that the search time, accuracy and response time for the question can be optimized. A minimum set of acoustic vectors extracted at the client are then sent via a communications channel to the server where additional acoustic vectors are derived. Using Hidden Markov Models (HMMs), and appropriate grammars and dictionaries conditioned by the course, chapter and section selections made by the student, the speech representing the user's query is fully decoding to text at the server. This text corresponding to the user's query is then simultaneously sent to a natural language engine and a database processor where an optimized SQL statement is constructed for a full-text search from a SQL database for a recordset of several stored questions that best matches the user's query. Further processing in the natural language engine narrows the search down to a single stored question. The answer that is paired to this single stored question is then retrieved from the file path and sent to the student computer in compressed form. At the student's computer, the answer is articulated using a text-to-speech engine in his or her native natural language. The system requires no training and can operate in several natural languages.

Abstract: A computer system and method is disclosed that transforms data for use in other applications. Several client workstations and servers are coupled together over a network. A client computer contains a user interface for performing the mapping and transformation. Data elements are mapped from a data source to a multi-dimensional cube. The multi-dimensional cube is transformed into a test recordset to determine if the data elements are mapped correctly. The mapping information is saved to a template. A server includes business logic for using the saved template to create a final recordset from the data source using the template. The server sends at least part of the recordset to a browser user interface on a client computer for display.

Abstract: The invention discloses an automatic extraction method of WEB structured information, belonging to the technical field of the internet. The method adopts an automatic data recordset extraction method and an automatic information block content identification extraction method and comprises the following steps of: firstly acquiring an HTML code of a page through a URL; preprocessing the HTML code to eliminate errors and irrelevant marks, and generating a DOMTree of the page; then extracting similar information blocks on the page; finally extracting a text template, and classifying the content of information items of the extracted information blocks. The invention aims at providing an extraction method of WEB information capable of being used universally and automated within a certain limit and can obviously enhance the extraction precision and the automation degree.