Abstract: An indexing system for tagging a media stream is provided. The indexing system includes a plurality of inputs for defining at least one tag. A tagging system assigns the tag to the media stream. A tag analysis system selectively distributes tags for review and editing by members of the collaborative group. A tag database stores the tag and the media stream. Retrieval architecture can search the database using the tags.

Abstract: A speaker verification system for use with a security system includes a data store containing a speaker voiceprint model developed from speaker utterances of a pass phrase. It also includes an audio input receptive of an audio input stream. It further includes a verification module adapted to match a sub-model portion of the voiceprint model to a sub-stream portion of the input stream and issue a speaker verification. The system strikes a balance between accuracy risk and user convenience by using continuous speech recognition, a lengthy pass phrase, and matching relative to duration of the spotted sub-portion, and relative to an amount of additional training to which the corresponding states of the model have been submitted. Thus, the system can achieve accurate speaker verifications, while speakers may enroll with reduced repetitions, use the system hands-free, and experience reduced requirements for speaking most or all of the pass phrase over time.

Abstract: The Gaussian Dynamic Time Warping model provides a hierarchical statistical model for representing an acoustic pattern. The first layer of the model represents the general acoustic space; the second layer represents each speaker space and the third layer represents the temporal structure information contained in each enrollment speech utterance, based on equally-spaced time intervals. These three layers are hierarchically developed: the second layer is derived from the first, and the third layer is derived from the second. The model is useful in speech processing application, particularly in applications such as word and speaker recognition, using a spotting recognition mode.

Abstract: An improved method is provided for enrolling with a resource security system. The method includes: providing an access code to a system user; accessing the resource security system using the access code; prompting the user to input a biometric feature which identifies the user; capturing a biometric feature associated with the user; and associating the captured biometric feature with the identity of the user for subsequent verification. The method further includes subsequently granting access to the secured resource based on biometric feature data input by the user.

Abstract: The voice binding system associates spoken commands of a user's choosing with the semantic path or sequence used to navigate through a menu structure associated with the electronic device. After storing this association, the user can later navigate to the tagged location in the menu structure by simply uttering the spoken command again. Spoken commands are stored during the record mode in a lexicon that is later used by the speech recognizer. The voice binding database stores associations of voice commands and semantic strings, where the semantic strings correspond to the menu text items found in the linked list associated with the devices menu.

Abstract: The audio source is spectrally shaped by filtering in the time domain to approximate or emulate a standardized or target microphone input channel. The background level is adjusted by adding noise to the time domain signal prior to the onset of speech to set a predetermined background noise level based on a predetermined target. The audio source is then monitored in real time and the signal-to-noise ratio is adjusted by adding noise to the time domain signal, in real time, to maintain a signal-to-noise ratio based on a predetermined target value. The normalized audio signal may be applied to both training speech and test speech. The resultant normalization minimizes the mismatch between training and testing and also improves other speech processing functions, such as speech endpoint detection.

Abstract: The language acquisition system assists the user in acquiring the language of an application. The system uses the dialogue context, a dialogue model and syntactic-semantic grammars to progressively build commands which, to the application program, are syntactically and semantically correct in the current context and which can be interpreted by the dialogue server which then controls the application program. The system is independent of any particular application language. The system is also multimodal and supports both speech and text input. A toolkit is provided to add this functionality to virtually any application program.