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 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 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. 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.