Systems and methods providing for secure voice print authentication over a network are disclosed herein. During an enrollment stage, a client's voice is recorded and characteristics of the recording are used to create and store a voice print. When an enrolled client seeks access to secure information over a network, a sample voice recording is created. The sample voice recording is compared to at least one voice print. If a match is found, the client is authenticated and granted access to secure information. Systems and methods providing for a dual use voice analysis system are disclosed herein. Speech recognition is achieved by comparing characteristics of words spoken by a speaker to one or more templates of human language words. Speaker identification is achieved by comparing characteristics of a speaker's speech to one or more templates, or voice prints. The system is adapted to increase or decrease matching constraints depending on whether speaker identification or speaker recognition is desired.

A mechanism is provided for validating the tone of an electronic communication being composed based on the recipients of the electronic communication. At least one tone of the electronic communication being composed by a sender and an identity of each of one or more recipients to whom the electronic communication is to be sent and the sender are identified. One or more previous electronic communications sent to or received from one or more of the one or more recipients and at least one tone of each of the one or more previous electronic communications are identified in order to generate one or more preferred tones. The tone of the electronic communication being composed is compared to the one or more preferred tones. Responsive to identifying a tone discrepancy between the electronic communication being composed and the one or more preferred tones, a notification is presented to the sender.

A system for operating an automobile comprising a transponder having a user interface to receive commands from a user and operating as a virtual assistant, wherein the commands comprise commands for operation of a door of the automobile and a microprocessor in the automobile responsive to the transponder. The system for operating an automobile further comprising a detector subsystem configured to determine a potential strike of an object based on a determined distance to the object, wherein the microprocessor receives a communication from the transponder and wherein the automobile is configured to send a command to a door of the automobile in response to the communication. Further, the system in the automobile is configured to avoid the potential strike determined by the detector system by limiting the operation of the door and producing an alert to a user as to the potential strike.

A system for operating an automobile comprising a transponder having a user interface to receive commands from a user and operating as a virtual assistant, wherein the commands comprise commands for operation of a door of the automobile and a microprocessor in the automobile responsive to the transponder. The system for operating an automobile further comprising a detector subsystem configured to determine a potential strike of an object based on a determined distance to the object, wherein the microprocessor receives a communication from the transponder and wherein the automobile is configured to send a command to a door of the automobile in response to the communication. Further, the system in the automobile is configured to avoid the potential strike determined by the detector system by limiting the operation of the door and producing an alert to a user as to the potential strike.

Input data may be classified using one or both of mutual information between segments and expected class scores. Input data to be classified may be segmented into an input sequence of segments. The input sequence of segments may be compared with a reference sequences of segments for a first class to generate a first class score indicating a similarity between the input data and the first class. The first class score may be computed by computing a probability mass function between input segments and reference segments and then computing a mutual information value from the probability mass function. The input data may then be classified using the first class score and/or class score for other classes. In some implementations, expected class scores may be used in making the classification decision.

The present invention is directed to a deep neural network (DNN) having a triplet network architecture, which is suitable to perform speaker recognition. In particular, the DNN includes three feed-forward neural networks, which are trained according to a batch process utilizing a cohort set of negative training samples. After each batch of training samples is processed, the DNN may be trained according to a loss function, e.g., utilizing a cosine measure of similarity between respective samples, along with positive and negative margins, to provide a robust representation of voiceprints.

The present invention is directed to a deep neural network (DNN) having a triplet network architecture, which is suitable to perform speaker recognition. In particular, the DNN includes three feed-forward neural networks, which are trained according to a batch process utilizing a cohort set of negative training samples. After each batch of training samples is processed, the DNN may be trained according to a loss function, e.g., utilizing a cosine measure of similarity between respective samples, along with positive and negative margins, to provide a robust representation of voiceprints.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing speaker identification. In some implementations, data identifying a media item including speech of a speaker is received. Based on the received data, one or more other media items that include speech of the speaker are identified. One or more search results are generated that each reference a respective media item of the one or more other media items that include speech of the speaker. The one or more search results are provided for display.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing speaker identification. In some implementations, data identifying a media item including speech of a speaker is received. Based on the received data, one or more other media items that include speech of the speaker are identified. One or more search results are generated that each reference a respective media item of the one or more other media items that include speech of the speaker. The one or more search results are provided for display.

A computer-implemented method for proactive fraudster exposure in a customer service center according to content analysis and voice biometrics analysis, is provided herein. The computer-implemented method includes: (i) performing a first type analysis to cluster the call interactions into ranked clusters and storing the ranked clusters in a clusters database; (ii) performing a second type analysis on a predefined amount of the highest ranked clusters, into ranked clusters and storing the ranked clusters; the first type analysis is a content analysis and the second type analysis is a voice biometrics analysis, or vice versa; (iii) retrieving from the ranked clusters, a list of fraudsters; and (iv) transmitting the list of potential fraudsters to an application to display to a user said list of potential fraudsters via a display unit.