System and method for speaker verification using short utterance enrollments
First Claim
1. A method for verifying an identity of a speaker, comprising:
- receiving feature vectors extracted from an utterance made by a speaker claiming an identity;
measuring dissimilarity between the feature vectors and a codebook associated with a version of the utterance known to be made by the identity;
analyzing the utterance to ascertain information about repeating occurrences of the feature vectors in the utterance;
comparing the information about repeating occurrences of feature vectors occurring in the utterance with information about repeating occurrences of feature vectors in a version of the utterance known to be made by the claimed identity;
assigning a penalty to the measured dissimilarity based on the comparison; and
determining whether to accept the speaker as the identity using the measured dissimilarity modified by the assigned penalty.
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Accused Products
Abstract
A system and method are disclosed for verifying an identity of a speaker. In accordance with one embodiment, feature vectors are received that were extracted from an utterance made by a speaker claiming an identity. Dissimilarity may be measured between the feature vectors and a codebook associated with a version of the utterance known to be made by the identity. The utterance may be further analyzed to ascertain information about repeating occurrences of the feature vectors in the utterance. The information about repeating occurrences of feature vectors occurring in the utterance may be compared to information about repeating occurrences of feature vectors in a version of the utterance known to be made by the claimed identity. Based on the comparison, a penalty may be assigned to the measured dissimilarity. Using the measured dissimilarity modified by the assigned penalty, a determination may be made as to whether to accept the speaker as the identity.
24 Citations
20 Claims
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1. A method for verifying an identity of a speaker, comprising:
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receiving feature vectors extracted from an utterance made by a speaker claiming an identity;
measuring dissimilarity between the feature vectors and a codebook associated with a version of the utterance known to be made by the identity;
analyzing the utterance to ascertain information about repeating occurrences of the feature vectors in the utterance;
comparing the information about repeating occurrences of feature vectors occurring in the utterance with information about repeating occurrences of feature vectors in a version of the utterance known to be made by the claimed identity;
assigning a penalty to the measured dissimilarity based on the comparison; and
determining whether to accept the speaker as the identity using the measured dissimilarity modified by the assigned penalty. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A system for verifying an identity of a speaker, comprising:
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logic that receives feature vectors extracted from an utterance made by a speaker claiming an identity;
logic that measures dissimilarity between the feature vectors and a codebook associated with a version of the utterance known to be made by the identity;
logic that analyzes the utterance to ascertain information about repeating occurrences of the feature vectors in the utterance;
logic that compares the information about repeating occurrences of feature vectors occurring in the utterance with information about repeating occurrences of feature vectors in a version of the utterance known to be made by the claimed identity;
logic that assigns a penalty to the measured dissimilarity based on the comparison; and
logic that determines whether to accept the speaker as the identity using the measured dissimilarity modified by the assigned penalty. - View Dependent Claims (16, 17, 18)
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19. A method, comprising:
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obtaining an utterance comprising a plurality of frames and having a plurality of feature vectors;
identifying the feature vectors present in each frame;
tabulating the presence of feature vectors by frame for the whole utterance;
identifying the number of instances each feature vector is repeated in the utterance;
calculating a total sum of all repeating instances in the utterance;
dividing the number of repeats for each feature vector by the total sum to obtain an averaged value for each feature vector; and
storing the information about the number of repeats for each feature vector in a reference log associated with the utterance. - View Dependent Claims (20)
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Specification