Personalizing a context-free grammar using a dictation language model
AssigneeMicrosoft Corporation
InventorsTimothy S. Paek, David M. Chickering, Eric Norman Badger, Qiang Wu
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AssigneeMicrosoft Corporation
InventorsTimothy S. Paek, David M. Chickering, Eric Norman Badger, Qiang Wu
Estimating the term…
Architecture for integrating and generating back-off grammars (BOG) in a speech recognition application for recognizing out-of-grammar (OOG) utterances and updating the context-free grammars (CFG) with the results. A parsing component identifies keywords and/or slots from user utterances and a grammar generation component adds filler tags before and/or after the keywords and slots to create new grammar rules. The BOG can be generated from these new grammar rules and can be used to process the OOG user utterances. By processing the OOG user utterances through the BOG, the architecture can recognize and perform the intended task on behalf of the user.
A system for generating a dictation language model in speech recognition applications, comprising:
A computer-implemented method for using a dictation language model to personalize a context-free grammar (CFG), comprising:
A computer-implemented system for generating a dictation language model in command-and-control speech recognition applications, comprising:
Dependencies are inferred from the claim text.
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Using context dependencies, e.g. language models: grammatical context, e.g. disambiguation of the recognition hypotheses based on word sequence rules
Speech classification or search: word spotting
Speech analysis techniques or speech synthesis
About 1 year 4 months of term left · ends 2 Mar 2028 (estimated)
This application is related to co-pending U.S. patent application Ser. No. 11/278,893, entitled, “AUGMENTING CONTEXT-FREE GRAMMARS WITH BACK-OFF GRAMMARS FOR PROCESSING OUT-OF-GRAMMAR UTTERANCES”, and filed on Apr. 6, 2006, the entirety of which is incorporated by reference herein.
Typical speech recognition applications (e.g., command-and-control (C&C) speech recognition) allow users to interact with a system by speaking commands and/or asking questions restricted to fixed, grammar-containing pre-defined phrases. While speech recognition applications have been commonplace in telephony and accessibility systems for many years, only recently have mobile devices had the memory and processing capacity to support not only speech recognition, but a whole range of multimedia functionalities that can be controlled by speech.
Furthermore, the ultimate goal of the speech recognition technology is to be able to produce a system that can recognize with 100% accuracy all of the words that are spoken by any person. However, even after years of research in this area, the best speech recognition software applications still cannot recognize speech with 100% accuracy. For example, most commercial speech recognition applications utilize context-free grammars for C&C speech recognition. Typically, these grammars are authored such that they achieve broad coverage of utterances while remaining relatively small for faster performance. As such, some speech recognition applications are able to recognize over 90% of the words, when spoken under specific constraints regarding content and/or acoustic training has been performed to recognize the speaker's speech characteristics.
FIG. 1 illustrates a block diagram of a system for generating a back-off grammar in accordance with an innovative aspect.
FIG. 2 illustrates a block diagram of a BOG generation system that further includes a processing component for processing an OOG utterance using the BOG.
FIG. 3 illustrates a block diagram of a grammar generating system including a personalization component for updating a CFG.
The innovation is now described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding thereof. It may be evident, however, that the innovation can be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate a description thereof.
As used in this application, the terms “component,” “handler,” “model,” “system,” and the like are intended to refer to a computer-related entity, either hardware, a combination of hardware and software, or software in execution. For example, a component can be, but is not limited to being, a process running on a processor, a processor, a hard disk drive, multiple storage drives (of optical and/or magnetic storage medium), an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a server and the server can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers.
Additionally, these components can execute from various computer readable media having various data structures stored thereon. The components may communicate via local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network such as the Internet with other systems via the signal). Computer components can be stored, for example, on computer-readable media including, but not limited to, an ASIC (application specific integrated circuit), CD (compact disc), DVD (digital video disk), ROM (read only memory), floppy disk, hard disk, EEPROM (electrically erasable programmable read only memory) and memory stick in accordance with the claimed subject matter.