Patents by Inventor Jason Pelecanos

Jason Pelecanos has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20230037085
    Abstract: Implementations disclosed herein are directed to techniques for selectively enabling and/or disabling non-transient storage of one or more instances of assistant interaction data for turn(s) of a dialog between a user and an automated assistant. Implementations are additionally or alternatively directed to techniques for retroactive wiping of non-transiently stored assistant interaction data from previous assistant interaction(s).
    Type: Application
    Filed: January 7, 2021
    Publication date: February 2, 2023
    Inventors: Fadi Biadsy, Johan Schalkwyk, Jason Pelecanos
  • Publication number: 20220366914
    Abstract: A speaker verification method includes receiving audio data corresponding to an utterance, processing the audio data to generate a reference attentive d-vector representing voice characteristics of the utterance, the evaluation ad-vector includes ne style classes each including a respective value vector concatenated with a corresponding routing vector. The method also includes generating using a self-attention mechanism, at least one multi-condition attention score that indicates a likelihood that the evaluation ad-vector matches a respective reference ad-vector associated with a respective user. The method also includes identifying the speaker of the utterance as the respective user associated with the respective reference ad-vector based on the multi-condition attention score.
    Type: Application
    Filed: May 16, 2021
    Publication date: November 17, 2022
    Applicant: Google LLC
    Inventors: Ignacio Lopez Moreno, Quan Wang, Jason Pelecanos, Yiling Huang, Mert Saglam
  • Publication number: 20220310098
    Abstract: A speaker verification method includes receiving audio data corresponding to an utterance, processing a first portion of the audio data that characterizes a predetermined hotword to generate a text-dependent evaluation vector, and generating one or more text-dependent confidence scores. When one of the text-dependent confidence scores satisfies a threshold, the operations include identifying a speaker of the utterance as a respective enrolled user associated with the text-dependent confidence score that satisfies the threshold and initiating performance of an action without performing speaker verification. When none of the text-dependent confidence scores satisfy the threshold, the operations include processing a second portion of the audio data that characterizes a query to generate a text-independent evaluation vector, generating one or more text-independent confidence scores, and determining whether the identity of the speaker of the utterance includes any of the enrolled users.
    Type: Application
    Filed: March 24, 2021
    Publication date: September 29, 2022
    Applicant: Google LLC
    Inventors: Roza Chojnacka, Jason Pelecanos, Quan Wang, Ignacio Lopez Moreno
  • Publication number: 20220157298
    Abstract: Techniques disclosed herein enable training and/or utilizing speaker dependent (SD) speech models which are personalizable to any user of a client device. Various implementations include personalizing a SD speech model for a target user by processing, using the SD speech model, a speaker embedding corresponding to the target user along with an instance of audio data. The SD speech model can be personalized for an additional target user by processing, using the SD speech model, an additional speaker embedding, corresponding to the additional target user, along with another instance of audio data. Additional or alternative implementations include training the SD speech model based on a speaker independent speech model using teacher student learning.
    Type: Application
    Filed: January 28, 2022
    Publication date: May 19, 2022
    Inventors: Ignacio Lopez Moreno, Quan Wang, Jason Pelecanos, Li Wan, Alexander Gruenstein, Hakan Erdogan
  • Publication number: 20220122614
    Abstract: A method for evaluating a verification model includes receiving a first and a second set of verification results where each verification result indicates whether a primary model or an alternative model verifies an identity of a user as a registered user. The method further includes identifying each verification result in the first and second sets that includes a performance metric. The method also includes determining a first score of the primary model based on a number of the verification results identified in the first set that includes the performance metric and determining a second score of the alternative model based on a number of the verification results identified in the second set that includes the performance metric. The method further includes determining whether a verification capability of the alternative model is better than a verification capability of the primary model based on the first score and the second score.
    Type: Application
    Filed: October 21, 2020
    Publication date: April 21, 2022
    Applicant: Google LLC
    Inventors: Jason Pelecanos, Pu-sen Chao, Yiling Huang, Quan Wang
  • Patent number: 11238847
    Abstract: Techniques disclosed herein enable training and/or utilizing speaker dependent (SD) speech models which are personalizable to any user of a client device. Various implementations include personalizing a SD speech model for a target user by processing, using the SD speech model, a speaker embedding corresponding to the target user along with an instance of audio data. The SD speech model can be personalized for an additional target user by processing, using the SD speech model, an additional speaker embedding, corresponding to the additional target user, along with another instance of audio data. Additional or alternative implementations include training the SD speech model based on a speaker independent speech model using teacher student learning.
    Type: Grant
    Filed: December 4, 2019
    Date of Patent: February 1, 2022
    Assignee: Google LLC
    Inventors: Ignacio Lopez Moreno, Quan Wang, Jason Pelecanos, Li Wan, Alexander Gruenstein, Hakan Erdogan
  • Publication number: 20210312907
    Abstract: Techniques disclosed herein enable training and/or utilizing speaker dependent (SD) speech models which are personalizable to any user of a client device. Various implementations include personalizing a SD speech model for a target user by processing, using the SD speech model, a speaker embedding corresponding to the target user along with an instance of audio data. The SD speech model can be personalized for an additional target user by processing, using the SD speech model, an additional speaker embedding, corresponding to the additional target user, along with another instance of audio data. Additional or alternative implementations include training the SD speech model based on a speaker independent speech model using teacher student learning.
    Type: Application
    Filed: December 4, 2019
    Publication date: October 7, 2021
    Inventors: Ignacio Lopez Moreno, Quan Wang, Jason Pelecanos, Li Wan, Alexander Gruenstein, Hakan Erdogan
  • Publication number: 20080208581
    Abstract: A system and method for speaker recognition speaker modelling whereby prior speaker information is incorporated into the modelling process, utilising the maximum a posteriori (MAP) algorithm and extending it to contain prior Gaussian component correlation information. Firstly a background model (10) is estimated. Pooled acoustic reference data (11) relating to a specific demographic of speakers (population of interest) from a given total population is then trained via the Expectation Maximization (EM) algorithm (12) to produce a background model (13). The background model (13) is adapted utilising information from a plurality of reference speakers (21) in accordance with the Maximum A Posteriori (MAP) criterion (22). Utilizing MAP estimation technique, the reference speaker data and prior information obtained from the background model parameters are combined to produce a library of adapted speaker models, namely Gaussian Mixture Models (23).
    Type: Application
    Filed: December 3, 2004
    Publication date: August 28, 2008
    Inventors: Jason Pelecanos, Subramanian Sridharan, Robert Vogt
  • Publication number: 20070256499
    Abstract: A method, system and program storage device are provided for machine diagnostics, detection and profiling using pressure waves, the method including profiling known sources, acquiring pressure wave data, analyzing the acquired pressure wave data, and detecting if the analyzed pressure wave data matches a profiled known source; the system including a processor, a pressure wave transducer in signal communication with the processor, a pressure wave analysis unit in signal communication with the processor, and a source or threat detection unit in signal communication with the processor; and the program storage device including program steps for profiling known sources, acquiring pressure wave data, analyzing the acquired pressure wave data, and detecting if the analyzed pressure wave data matches a profiled known source.
    Type: Application
    Filed: April 21, 2006
    Publication date: November 8, 2007
    Inventors: Jason Pelecanos, Douglas Heintzman, Jiri Navratil, Ganesh Ramaswamy
  • Publication number: 20070239441
    Abstract: A method and system for speaker recognition and identification includes transforming features of a speaker utterance in a first condition state to match a second condition state and provide a transformed utterance. A discriminative criterion is used to generate a transform that maps an utterance to obtain a computed result. The discriminative criterion is maximized over a plurality of speakers to obtain a best transform for recognizing speech and/or identifying a speaker under the second condition state. Speech recognition and speaker identity may be determined by employing the best transform for decoding speech to reduce channel mismatch.
    Type: Application
    Filed: March 29, 2006
    Publication date: October 11, 2007
    Inventors: Jiri Navratil, Jason Pelecanos, Ganesh Ramaswamy
  • Publication number: 20060294390
    Abstract: Methods and apparatus are provided for sequential authentication of a user that employ one or more error rates characterizing each security challenge. According to one aspect of the invention, a user is challenged with at least one knowledge challenge to obtain an intermediate authentication result; and the user challenges continue until a cumulative authentication result satisfies one or more criteria. The intermediate authentication result is based, for example, on one or more of false accept and false reject error probabilities for each knowledge challenge. A false accept error probability describes a probability of a different user answering the knowledge challenge correctly. A false reject error probability describes a probability of a genuine user not answering the knowledge challenge correctly. The false accept and false reject error probabilities can be adapted based on field data or known information about a given challenge.
    Type: Application
    Filed: June 23, 2005
    Publication date: December 28, 2006
    Applicant: International Business Machines Corporation
    Inventors: Jiri Navratil, Ryan Osborn, Jason Pelecanos, Ganesh Ramaswamy, Ran Zilca
  • Publication number: 20060111905
    Abstract: There is provided an apparatus for providing a Text Independent (TI) speaker recognition mode in a Text Dependent (TD) Hidden Markov Model (HMM) speaker recognition system and/or a Text Constrained (TC) HMM speaker recognition system. The apparatus includes a Gaussian Mixture Model (GMM) generator and a Gaussian weight normalizer. The GMM generator is for creating a GMM by pooling Gaussians from a plurality of HMM states. The Gaussian weight normalizer is for normalizing Gaussian weights with respect to the plurality of HMM states.
    Type: Application
    Filed: November 22, 2004
    Publication date: May 25, 2006
    Inventors: Jiri Navratil, James Nealand, Jason Pelecanos, Ganesh Ramaswamy, Ran Zilca
  • Publication number: 20050273339
    Abstract: A method and apparatus for remote access to a target application is disclosed where a system administrator may establish telephonic contact with an interactive voice response system and obtain access to the target application by speech communication. The interactive response system may authenticate the system administrator by implementing various measures including biometric measures. Once access is granted, the interactive response system may broker a communication between the target application using text/data and the system administrator using natural language.
    Type: Application
    Filed: June 2, 2004
    Publication date: December 8, 2005
    Inventors: Upendra Chaudhari, Ryan Osborn, Jason Pelecanos, Ganesh Ramaswamy, Ran Zilca
  • Publication number: 20050232470
    Abstract: Methods and arrangements for assessing the identity of an individual. Input is accepted from an individual, and at least one user group is attributed to the individual. This attributing is repeated until the identity of the individual is assessed.
    Type: Application
    Filed: March 31, 2004
    Publication date: October 20, 2005
    Applicant: IBM Corporation
    Inventors: Upendra Chaudhari, Jiri Navratil, Jason Pelecanos, Ganesh Ramaswamy, Ran Zilca