Abstract: A multimedia search apparatus and method for searching multimedia content using speaker detection to segment the multimedia content. The multimedia search apparatus receives a search request from a user device. The search request identifies the target speaker for which the search is to be conducted. Based on the search request, the multimedia search apparatus retrieves multimedia content from a multimedia database. The multimedia search apparatus retrieves models, such as Gaussian Mixture Models (GMMs), from a model storage device, corresponding to the target speaker and background data. Based on the retrieved models, the multimedia search device searches the multimedia data of the multimedia content and segments the multimedia data. The segments are identified by calculating an average normalized score for a block of frames of the multimedia data and determining if the average normalized score for the block of frames exceeds one or more predetermined thresholds.

Abstract: A multimedia search apparatus and method for searching multimedia content using speaker detection to segment the multimedia content. The multimedia search apparatus receives a search request from a user device. The search request identifies the target speaker for which the search is to be conducted. Based on the search request, the multimedia search apparatus retrieves multimedia content from a multimedia database. The multimedia search apparatus retrieves models, such as Gaussian Mixture Models (GMMs), from a model storage device, corresponding to the target speaker and background data. Based on the retrieved models, the multimedia search device searches the multimedia data of the multimedia content and segments the multimedia data. The segments are identified by calculating an average normalized score for a block of frames of the multimedia data and determining if the average normalized score for the block of frames exceeds one or more predetermined thresholds.

Abstract: A speaker identification system is provided that constructs speaker models using a discriminant analysis technique where the data in each class is modeled by Gaussian mixtures. The speaker identification method and apparatus determines the identity of a speaker, as one of a small group, based on a sentence-length password utterance. A speaker's utterance is received and a sequence of a first set of feature vectors are computed based on the received utterance. The first set of feature vectors are then transformed into a second set of feature vectors using transformations specific to a particular segmentation unit, and likelihood scores of the second set of feature vectors are computed using speaker models trained using mixture discriminant analysis. The likelihood scores are then combined to determine an utterance score and the speaker's identity is validated based on the utterance score. The speaker identification method and apparatus also includes training and enrollment phases.

Abstract: A multimedia search apparatus and method for searching multimedia content using speaker detection to segment the multimedia content. The multimedia search apparatus receives a search request from a user device. The search request identifies the target speaker for which the search is to be conducted. Based on the search request, the multimedia search apparatus retrieves multimedia content from a multimedia database. The multimedia search apparatus retrieves models, such as Gaussian Mixture Models (GMMs), from a model storage device, corresponding to the target speaker and background data. Based on the retrieved models, the multimedia search device searches the audio data of the multimedia content and segments the audio data. The segments are identified by calculating an average normalized score for a block of frames of the audio data and determining if the average normalized score for the block of frames exceeds one or more predetermined thresholds.

Abstract: A speaker identification system is provided that constructs speaker models using a discriminant analysis technique where the data in each class is modeled by Gaussian mixtures. The speaker identification method and apparatus determines the identity of a speaker, as one of a small group, based on a sentence-length password utterance. A speaker's utterance is received and a sequence of a first set of feature vectors are computed based on the received utterance. The first set of feature vectors are then transformed into a second set of feature vectors using transformations specific to a particular segmentation unit, and likelihood scores of the second set of feature vectors are computed using speaker models trained using mixture discriminant analysis. The likelihood scores are then combined to determine an utterance score and the speaker's identity is validated based on the utterance score. The speaker identification method and apparatus also includes training and enrollment phases.

Abstract: A speaker identification system includes a speaker-independent phrase recognizer. The speaker-independent phrase recognizer scores a password utterance against all the sets of phonetic transcriptions in a lexicon database to determine the N best speaker-independent scores, determines the N best sets of phonetic transcriptions based on the N best speaker-independent scores, and determines the N best possible identities. A speaker-dependent phrase recognizer retrieves the hidden Markov model corresponding to each of the N best possible identities, and scores the password utterance against each of the N hidden Markov models to generate a speaker-dependent score for each of the N best possible identities. A score processor coupled to the outputs of the speaker-independent phrase recognizer and the speaker-dependent phrase recognizer determines a putative identity. A verifier coupled to the score processor authenticates the determined putative identity.