Abstract: Computer implemented speech processing generates one or more pronunciations of an input word in a first language by a non-native speaker of the first language who is a native speaker of a second language. The input word is converted into one or more pronunciations. Each pronunciation includes one or more phonemes selected from a set of phonemes associated with the second language. Each pronunciation is associated with the input word in an entry in a computer database. Each pronunciation in the database is associated with information identifying a pronunciation language and/or a phoneme language.

Abstract: A system and method for an automatic set-up of speech recognition engines may include a speech recognizer configured to perform speech recognition procedures to identify input speech data according to one or more operating parameters. A merit manager may be utilized to automatically calculate merit values corresponding to the foregoing recognition procedures. These merit values may incorporate recognition accuracy information, recognition speed information, and a user-specified weighting factor that shifts the relative effect of the recognition accuracy information and the recognition speed information on the merit values. The merit manager may then automatically perform a merit value optimization procedure to select operating parameters that correspond to an optimal one of the merit values.

Abstract: A system and method for effectively performing speech recognition procedures includes enhanced demiphone acoustic models that a speech recognition engine utilizes to perform the speech recognition procedures. The enhanced demiphone acoustic models each have three states that are collectively arranged to form a preceding demiphone and a succeeding demiphone. An acoustic model generator may utilize a decision tree for analyzing speech context information from a training database. The acoustic model generator then effectively configures each of the enhanced demiphone acoustic models as either a succeeding-dominant enhanced demiphone acoustic model or a preceding-dominant enhanced demiphone acoustic model to accurately model speech characteristics.

Abstract: A system and method for performing a refinement procedure to effectively implement a speech recognition dictionary for spontaneous speech recognition may include a problematic word identifier configured to divide vocabulary words from an initial speech recognition dictionary into problematic words and non-problematic words according to pre-defined identification criteria. A candidate generator may analyze the problematic words to produce one or more pronunciation candidates for each of the problematic words. An optimization module may then perform an optimization process for refining one or more pronunciation candidates according to certain optimization criteria to thereby generate optimized problematic pronunciations. A dictionary refinement manager may finally combine the optimized problematic pronunciations with non-problematic pronunciations of the non-problematic words to produce a refined speech recognition dictionary for use by the speech recognition system.

Abstract: A system and method for utilizing speech recognition to efficiently perform data indexing procedures includes an authoring module that coordinates an authoring procedure for creating an index file that has pattern word sets corresponding to data objects stored in a memory of a host electronic device. The pattern word sets are generated with a speech recognition engine that transforms spoken data descriptions into text data descriptions for creating the pattern word sets. The pattern word sets are associated in the index file with data object identifiers that uniquely identify the corresponding data objects. A retrieval module manages a retrieval procedure in which the speech recognition engine converts a spoken data request into a text data request. The retrieval module compares the text data request and the pattern word sets to identify a requested object identifier for locating a requested data object from among the data objects stored in the memory of the host electronic device.

Abstract: Consumer electronic devices have been developed with enormous information processing capabilities, high quality audio and video outputs, large amounts of memory, and may also include wired and/or wireless networking capabilities. Additionally, relatively unsophisticated and inexpensive sensors, such as microphones, video camera, GPS or other position sensors, when coupled with devices having these enhanced capabilities, can be used to detect subtle features about users and their environments. A variety of audio, video, simulation and user interface paradigms have been developed to utilize the enhanced capabilities of these devices. These paradigms can be used separately or together in any combination. One paradigm automatically creating user identities using speaker identification. Another paradigm includes a control button with 3-axis pressure sensitivity for use with game controllers and other input devices.

Abstract: Methods for optimizing grammar structure for a set of phrases to be used in speech recognition during a computing event are provided. One method includes receiving a set of phrases, the set of phrases being relevant for the computing event and the set of phrases having a node and link structure. Also included is identifying redundant nodes by examining the node and link structures of each of the set of phrases so as to generate a single node for the redundant nodes. The method further includes examining the node and link structures to identify nodes that are capable of being vertically grouped and grouping the identified nodes to define vertical word groups. The method continues with fusing nodes of the set of phrases that are not vertically grouped into fused word groups. Wherein the vertical word groups and the fused word groups are linked to define an optimized grammar structure.

Abstract: The present invention comprises a system and method for speech verification using a robust confidence measure, and includes a speech verifier which compares a confidence measure for a recognized word to a predetermined threshold value in order to determine whether the recognized word is valid, where a recognized word corresponds to a word model that produces a highest recognition score. In accordance with the present invention, the foregoing confidence measure may be calculated using the recognition score for the recognized word, a background score of a worst recognition candidate, and a pseudo filler score that may be based upon selected average recognition scores from an N-best list of recognition candidates.

Abstract: A system and method is provided that randomly generates text with a given structure. The structure is taken from a number of learning examples. The structure of training examples is captured by word classification and the definition of the relationships between word classes in a given language. The text generated with this procedure is intended to replicate the information given by the original learning examples. The resulting text may be used to better model the structure of a language in a stochastic language model.

Abstract: The present invention comprises a system and method for speech verification using an efficient confidence measure, and includes a speech verifier which compares a confidence measure for a recognized word to a predetermined threshold value in order to determine whether the recognized word is valid, where a recognized word corresponds to a word model that produces a highest recognition score. In accordance with the present invention, the foregoing confidence measure may be calculated using the recognition score for the recognized word and a pseudo filler score that may be based upon selected average recognition scores from an N-best list of recognition candidates.

Abstract: A system and method for performing speech recognition in cyclostationary noise environments includes a characterization module that may access original cyclostationary noise from an intended operating environment of a speech recognition device. The characterization module may then convert the original cyclostationary noise into target stationary noise which retains characteristics of the original cyclostationary noise. A conversion module may then generate a modified training database by utilizing the target stationary noise to modify an original training database that was prepared for training a recognizer in the speech recognition device. A training module may then train the recognizer with the modified training database to thereby optimize speech recognition procedures in cyclostationary noise environments.

Abstract: A system and method for an automatic set-up of speech recognition engines may include a speech recognizer configured to perform speech recognition procedures to identify input speech data according to one or more operating parameters. A merit manager may be utilized to automatically calculate merit values corresponding to the foregoing recognition procedures. These merit values may incorporate recognition accuracy information, recognition speed information, and a user-specified weighting factor that shifts the relative effect of the recognition accuracy information and the recognition speed information on the merit values. The merit manager may then automatically perform a merit value optimization procedure to select operating parameters that correspond to an optimal one of the merit values.

Abstract: A system and method is provided that randomly generates text with a given structure. The structure is taken from a number of learning examples. The structure of training examples is captured by word classification and the definition of the relationships between word classes in a given language. The text generated with this procedure is intended to replicate the information given by the original learning examples. The resulting text may be used to better model the structure of a language in a stochastic language model.

Abstract: The present invention comprises a system and method for speech verification using a robust confidence measure, and includes a speech verifier which compares a confidence measure for a recognized word to a predetermined threshold value in order to determine whether the recognized word is valid, where a recognized word corresponds to a word model that produces a highest recognition score. In accordance with the present invention, the foregoing confidence measure may be calculated using the recognition score for the recognized word, a background score, and a pseudo filler score that may be based upon selected average recognition scores from an N-best list of recognition candidates.

Abstract: A system and method for performing speech recognition in cyclostationary noise environments includes a characterization module that may access original cyclostationary noise from an intended operating environment of a speech recognition device. The characterization module may then convert the original cyclostationary noise into target stationary noise which retains characteristics of the original cyclostationary noise. A conversion module may then generate a modified training database by utilizing the target stationary noise to modify an original training database that was prepared for training a recognizer in the speech recognition device. A training module may then train the recognizer with the modified training database to thereby optimize speech recognition procedures in cyclostationary noise environments.

Abstract: The present invention comprises a system and method for speech verification using an efficient confidence measure, and includes a speech verifier which compares a confidence measure for a recognized word to a predetermined threshold value in order to determine whether the recognized word is valid, where a recognized word corresponds to a word model that produces a highest recognition score. In accordance with the present invention, the foregoing confidence measure may be calculated using the recognition score for the recognized word and a pseudo filler score that may be based upon selected average recognition scores from an N-best list of recognition candidates.