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1.发明申请公开(公告)号：US20190164557A1
公开(公告)日：2019-05-30
申请号：US16203077
申请日：2018-11-28
申请人： ILLUMA Labs Inc.
发明人： Milind BORKAR
摘要： A system and method for efficient universal background model (UBM) training for speaker recognition, including: receiving an audio input, divisible into a plurality of audio frames, wherein at least a first audio frame of the plurality of audio frames includes an audio sample having a length above a first threshold extracting at least one identifying feature from the first audio frame and generating a feature vector based on the at least one identifying feature; generating an optimized training sequence computation based on the feature vector and a Gaussian Mixture Model (GMM), wherein the GMM is associated with a plurality of components, wherein each of the plurality of components is defined by a covariance matrix, a mean vector, and a weight vector; and updating any of the associated components of the GMM based on the generated optimized training sequence computation.
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公开(公告)号：US20210201919A1
公开(公告)日：2021-07-01
申请号：US17201987
申请日：2021-03-15
申请人： ILLUMA Labs Inc.
发明人： Milind BORKAR
摘要： A method and system for secure speaker authentication between a caller device and a first device using an authentication server are provided. The system comprises extracting features into a feature matrix from an incoming audio call; generating a partial i-vector, wherein the partial i-vector includes a first low-order statistic; sending the partial i-vector to the authentication server; and receiving from the authentication server a match score generated based on a full i-vector and another i-vector being stored on the authentication server, wherein the full i-vector is generated from the partial i-vector.
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3.发明申请公开(公告)号：US20210043215A1
公开(公告)日：2021-02-11
申请号：US17081394
申请日：2020-10-27
申请人： ILLUMA Labs Inc.
发明人： Milind BORKAR
摘要： A system and method for efficient universal background model (UBM) training for speaker recognition, including: receiving an audio input, divisible into a plurality of audio frames, wherein at least a first audio frame of the plurality of audio frames includes an audio sample having a length above a first threshold extracting at least one identifying feature from the first audio frame and generating a feature vector based on the at least one identifying feature; generating an optimized training sequence computation based on the feature vector and a Gaussian Mixture Model (GMM), wherein the GMM is associated with a plurality of components, wherein each of the plurality of components is defined by a covariance matrix, a mean vector, and a weight vector; and updating any of the associated components of the GMM based on the generated optimized training sequence computation.
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公开(公告)号：US20210201917A1
公开(公告)日：2021-07-01
申请号：US17201619
申请日：2021-03-15
申请人： ILLUMA Labs Inc.
发明人： Milind BORKAR
IPC分类号： G10L17/04
摘要： A system and method for improving T-matrix training for speaker recognition, comprising receiving an audio input, divisible into a plurality of audio frames including at least an audio sample of a human speaker; generating for each audio frame a feature vector; generating for a first plurality of feature vectors centered statistics of at least a zero order and a first order; generating a first i-vector, the first i-vector representing the human speaker; and generating an optimized T-matrix training sequence computation, based on at least the first i-vector.
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公开(公告)号：US20190244622A1
公开(公告)日：2019-08-08
申请号：US16385511
申请日：2019-04-16
申请人： ILLUMA Labs Inc.
发明人： Milind BORKAR
摘要： A system and method for enrolling a speaker in a speaker authentication and identification system (AIS), the method comprising: generating a user account, the user account comprising: a user identifier based on one or more metadata elements associated with an audio input received from an end device; generating a first i-vector from an audio frame of the audio input, a trained T-matrix, and a Universal Background Model (UBM), wherein the first i-vector generation comprises an optimized computation; and associating the user account with the first i-vector.
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公开(公告)号：US20190198025A1
公开(公告)日：2019-06-27
申请号：US16290399
申请日：2019-03-01
申请人： ILLUMA Labs Inc.
发明人： Milind BORKAR
IPC分类号： G10L17/04
摘要： A system and method for improving T-matrix training for speaker recognition are provided. The method includes receiving an audio input, divisible into a plurality of audio frames, wherein at least a first audio frame includes an audio sample of a human speaker, the sample having a length above a first threshold; generating for each audio frame a feature vector; generating for a first plurality of feature vectors centered statistics of at least a zero order and a first order; generating a first i-vector, the first i-vector representing the human speaker; generating an optimized T-matrix training sequence computation, based on the first i-vector, an initialized T-matrix, the centered statistics, and a Gaussian mixture model (GMM) of a trained universal background model (UBM).
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