Method and apparatus for multi-pass speech recognition. An input device receives spoken input. A processor performs a first pass speech recognition technique on the spoken input and forms first pass results. The first pass results include a number of alternative speech expressions, each having an assigned score related to the certainty that the corresponding expression correctly matches the spoken input. The processor selectively performs a second pass speech recognition technique on the spoken input according to the first pass results. Preferably, the second pass attempts to correctly match the spoken input to only those expressions which were identified during the first pass. Otherwise, if one of the expressions identified by the first pass is assigned a score higher than a predetermined threshold (e.g., 95%), the second pass is not performed. Because the second pass is performed only when necessary, the invention recognizes speech with a faster average speed for a given accuracy in comparison to prior systems. Alternately, the first pass results identify a characteristic of the spoken input. The characteristic can be the gender of the speaker or a type of telephone the speaker is calling from. In which case, the second pass speech recognition technique is selected from a plurality of speech recognition techniques according to the characteristic identified by the first pass. Because the selected second pass technique is specific to the characteristic of the spoken input, the second pass technique can perform speech recognition faster for a given accuracy than a technique which is not specific.
A multiple pass speech recognition method includes a first pass and a second pass. The first pass recognizes an input speech signal to generate a first pass result. The second pass generates a first grammar having a portion set to match a first part of the input speech signal, based upon the context of the first pass result, and generate a second pass result. The method may further include a third pass grammar limiting the second part of the input speech signal to the second pass result. The third pass grammar includes a model corresponding to the first part of the input speech signal and varying within the second pass result. The third pass compares the first part of the input speech signal to the model while limiting the second part of the input speech signal to the second pass result.
A speech recognition method and system for use in a vehicle navigation system utilize grammar weighted based upon geographical information regarding the locations corresponding to the tokens in the grammars and/or the location of the vehicle for which the vehicle navigation system is used, in order to enhance the performance of speech recognition. The geographical information includes the distances between the vehicle location and the locations corresponding to the tokens, as well as the size, population, and popularity of the locations corresponding to the tokens.
This invention concerns a method and system for monitoring an automated dialog system for the automatic recognition of language understanding errors based on a user's input communications in a dialog with the user. The probability of conducting a successful dialog with the user is determined based, at least in part, on understanding data from at least one prior dialog exchange of the dialog.
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.
A speech-enabled internet based computing system includes a configurable speech recognition engine used for interacting with content on a web accessible page. The speech recognition engine is distributed across a client and server architecture, and is adaptive so that speech processing operations can be allocated as needed between the two. 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 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.
