Phoenix Solutions, Inc.

Nuance Communications, Inc.

Hewlett-Packard Company

Ian Bennett

Kishor Morkhandikar

Bandi Ramesh Babu

Pallaki Gururaj

Richard D Pering

Richard A Baumgartner

John N Dukes

George A Fisher

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.

Multi-language speech recognition system

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.

Distributed real time speech recognition system

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.

Speech recognition system interactive agent

A speech recognition engine is configured to permit partial or full recognition of an utterance at a client device and/or a server device. This allows for support for client devices having differing computing capabilities. Natural language operations can also be supported as desired. A user can thus interact with content also accessible at a web page and select items of interest using speech as a mode of input. Dynamic grammars can assist in the recognition operations to improve speed and comprehension.

Method of interacting through speech with a web-connected server

An intelligent query system for processing voiced-based queries is disclosed, which uses semantic based processing to identify the question posed by the user by understanding the meaning of the user's utterance. Based on identifying the meaning of the utterance, the system selects a single answer that best matches the user's query. The answer that is paired to this single question is then retrieved and presented to the user. 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.

Semantic decoding of user queries

A prosody analyzer enhances the interpretation of natural language utterances. The analyzer is distributed over a client/server architecture, so that the scope of emotion recognition processing tasks can be allocated on a dynamic basis based on processing resources, channel conditions, client loads etc. The partially processed prosodic data can be sent separately or combined with other speech data from the client device and streamed to a server for a real-time response. Training of the prosody analyzer with real world expected responses improves emotion modeling and the real-time identification of potential features such as emphasis, intent, attitude and semantic meaning in the speaker's utterances.

Emotion detection device and method for use in distributed systems

An intelligent query system for processing voiced-based queries is disclosed, which uses a combination of both statistical and semantic based processing to identify the question posed by the user by understanding the meaning of the user's utterance. Based on identifying the meaning of the utterance, the system selects a single answer that best matches the user's query. The answer that is paired to this single question is then retrieved and presented to the user. 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.

Statistical language model trained with semantic variants

Natural language speech lattice containing semantic variants

A network based interactive speech system responds in real-time to speech-based queries addressed to a set of topic entries. A best matching response is provided based on speech recognition processing and natural language processing performed on recognized speech utterances to identify a selected set of phrases related to the set of topic entries. Another routine converts the selected set of phrases into a search query suitable for identifying a first group of one or more topic entries corresponding to the speech-based query. The words/phrases can be assigned different weightings and can include entries which are not actually in the set of topic entries.

Network based interactive speech recognition system

A client device incorporates partial speech recognition for recognizing a spoken query by a user. The full recognition process is distributed over a client/server architecture, so that the amount of partial recognition signal processing tasks can be allocated on a dynamic basis based on processing resources, channel conditions, etc. Partially processed speech data from the client device can be streamed to a server for a real-time response. Additional natural language processing operations can also be performed to implement sentence recognition functionality.

Partial speech processing device and method for use in distributed systems

A speech-enabled WWW based computing system allows a user to interact with content associated with a web page and select items of interest using speech as a mode of input. Dynamic grammars can assist in the recognition operations to improve speed and comprehension.

Internet based speech recognition system with dynamic grammars

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 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. Both statistical and semantic decoding are used to assist and improve the performance of the query recognition.

Query engine for processing voice based queries including semantic decoding

Speech based query system using semantic decoding

Candidate answers responsive to a user query are analyzed using a natural language engine to determine appropriate answers from an electronic database. The system and methods are useful for Internet based search engines, as well as distributed speech recognition systems such as a client-server system. The latter are typically implemented on an intranet or over the Internet based on user queries at his/her computer, a PDA, or a workstation using a speech input interface.

System and method for natural language processing of query answers

A speech-enabled internet based computing system includes a configurable speech recognition engine which allows support for client devices having differing computing capabilities. Natural language operations can also be supported as desired.

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Palo Alto, CA, United States of America

Ian Bennett