Abstract: A speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. A number of different speech models for different natural languages are used to support and detect a natural language spoken by a user. In some implementations an interactive electronic agent responds in the user's native language to facilitate an real-time, human like dialog.

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.

Abstract: A speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. A number of different speech models for different languages are used to support and detect a language spoken by a user. In some implementations an interactive electronic agent responds in the user's language to facilitate a real-time, human like dialogue.

Abstract: Methods and systems for performing speech recognition using an electronic interactive agent are disclosed. In embodiments of the invention, an electronic agent is presented in a form perceptible to a user. The electronic agent is used to solicit speech input from a user and to respond to the user's recognized speech, and mimics the behavior of a human agent in a natural language query session with the user. The electronic agent may be implemented in a distributed speech recognition system in which speech recognition tasks are divided between client and server.

Abstract: A real-time speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. Both the client and server can dedicate a variable number of processing resources for performing speech recognition functions. The partitioning of responsibility for speech recognition operations can be done on a client by client or connection by connection basis.

Abstract: A speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. A number of different speech models for different natural languages are used to support and detect a natural language spoken by a user. In some implementations an interactive electronic agent responds in the user's native language to facilitate an real-time, human like dialogue.

Abstract: A speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. A number of different speech models for different natural languages are used to support and detect a natural language spoken by a user. In some implementations an interactive electronic agent responds in the user's native language to facilitate an real-time, human like dialogue.

Abstract: A speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. A number of different speech models for different languages are used to support and detect a language spoken by a user. In some implementations an interactive electronic agent responds in the user's language to facilitate a real-time, human like dialogue.

Abstract: A speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. A number of different speech models for different languages are used to support and detect a language spoken by a user. In some implementations an interactive electronic agent responds in the user's language to facilitate a real-time, human like dialogue.

Abstract: A speech recognition system uses speech recognition models which are specifically trained and optimized for users residing in a particular geographic area or region. The speech models are trained with samples of word variants expected to be used in a natural language by representative members of a population associated with the geographic region or community of users. The speech recognition system is configured to have a real-time response that imitates a dialogue with a human operator.

Abstract: A real-time speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. Both the client and server can dedicate a variable number of processing resources for performing speech recognition functions. The partitioning of responsibility for speech recognition operations can be done on a client by client or connection by connection basis.

Abstract: A real-time speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. Both the client and server can dedicate a variable number of processing resources for performing speech recognition functions. In some implementations the partitioning of responsibility for speech recognition operations can be done on a client by client or query by query basis.

Abstract: A speech recognition system uses speech recognition models which are specifically trained and optimized for users residing in a particular geographic area or region. The speech models are trained with samples of word variants expected to be used in a natural language by representative members of a population associated with the geographic region or community of users. The speech recognition system is configured to have a real-time response that imitates a dialogue with a human operator.

Abstract: A speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. A number of different speech models for different languages are used to support and detect a language spoken by a user. In some implementations an interactive electronic agent responds in the user's language to facilitate a real-time, human like dialogue.

Abstract: A real-time speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. Both the client and server can dedicate a variable number of processing resources for performing speech recognition functions. In some implementations the partitioning of responsibility for speech recognition operations can be done on a client by client or query by query basis.

Abstract: A speech recognition system includes distributed processing across a client and server for recognizing a spoken query by a user. A number of different speech models for different natural languages are used to support and detect a natural language spoken by a user. In some implementations an interactive electronic agent responds in the user's native language to facilitate an real-time, human like dialogue.

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.

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.

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.

Abstract: An intelligent query system for processing voiced-based queries is disclosed. This distributed client-server system, typically implemented on an intranet or over the Internet accepts a user's queries at his/her computer, PDA or workstation using a speech input interface. After converting the user's query from speech to text, a 2-step algorithm employing a natural language engine, a database processor and a full-text SQL database is implemented to find a single answer that best matches the user's query. The system, as implemented, accepts environmental variables selected by the user and is scalable to provide answers to a variety and quantity of user-initiated queries.