Abstract: This disclosure provides systems, methods and apparatuses for machine learning. In some implementations, a pre-processing system may identify one or more special features in an input dataset and may generate one or more pruned datasets, respectively, based on the identified special features. The pre-processing system maps each of the pruned datasets to one or more predictions and selectively removes the values associated with one or more special features from the input dataset based on the mapping. In some other implementations, a pre-processing system may map each of the feature sets in an input dataset to multiple predictions in accordance with multiple machine learning algorithms. The pre-processing system evaluates a performance of each of the mappings and selects one of the machine learning algorithms to be used to train the machine learning model based on the performance of each mapping.

Abstract: A method including generating a captured facial object and a captured pose from a captured image. The method also includes obtaining a base facial object and a base pose from a base image. The method also includes generating base pose angles using the captured pose, and captured pose angles using the captured pose. The method also includes obtaining selected base images using the base pose angles and the base facial object. The method also includes generating selected captured images using the captured pose angles and the captured facial object. The method also includes comparing the selected base images to the selected captured images to establish a comparison. The method also includes outputting a match output using the comparison.

Abstract: This disclosure relates to generating a comprehensive set of synthetic utterances. An example system is configured to provide an input utterance to a plurality of synthetic utterance generation pipelines in parallel. Each of the plurality of synthetic utterance generation pipelines include one or more utterance synthesizers. For example, one or more pipelines may use a synthesizer chain that includes a plurality of synthesizers in parallel. The plurality of synthetic utterance generation pipelines generates synthetic utterances, which may be stored in a database after evaluating the similarity between the original input utterance and each resulting synthetic utterance. For example, a synthetic utterance may be retained if the cosine similarity between the input and synthetic utterances is less than a predetermined threshold.

Abstract: Systems and methods for verifying an identity of a party to a video call are disclosed. An example method may be performed by one or more processors of a verification system and include storing first facial encodings, each of the first facial encodings associated with one or more images of a corresponding registered user of a plurality of registered users associated with the verification system, receiving, during a video call associated with a specified registered user of the plurality of registered users, a second facial encoding associated with one or more images of a person participating in the video call, the second facial encoding received from a device with which the person uses to participate in the video call, identifying, among the first facial encodings, a first facial encoding corresponding to the specified registered user, and determining whether the person participating in the video call is the specified registered user.

Abstract: A method including generating a captured facial object and a captured pose from a captured image. The method also includes obtaining a base facial object and a base pose from a base image. The method also includes generating base pose angles using the captured pose, and captured pose angles using the captured pose. The method also includes obtaining selected base images using the base pose angles and the base facial object. The method also includes generating selected captured images using the captured pose angles and the captured facial object. The method also includes comparing the selected base images to the selected captured images to establish a comparison. The method also includes outputting a match output using the comparison.

Abstract: This disclosure provides systems, methods and apparatuses for machine learning. In some implementations, a pre-processing system may identify one or more special features in an input dataset and may generate one or more pruned datasets, respectively, based on the identified special features. The pre-processing system maps each of the pruned datasets to one or more predictions and selectively removes the values associated with one or more special features from the input dataset based on the mapping. In some other implementations, a pre-processing system may map each of the feature sets in an input dataset to multiple predictions in accordance with multiple machine learning algorithms. The pre-processing system evaluates a performance of each of the mappings and selects one of the machine learning algorithms to be used to train the machine learning model based on the performance of each mapping.

Abstract: Systems and methods for verifying an identity of a party to a video call are disclosed. An example method may be performed by one or more processors of a verification system and include storing first facial encodings, each of the first facial encodings associated with one or more images of a corresponding registered user of a plurality of registered users associated with the verification system, receiving, during a video call associated with a specified registered user of the plurality of registered users, a second facial encoding associated with one or more images of a person participating in the video call, the second facial encoding received from a device with which the person uses to participate in the video call, identifying, among the first facial encodings, a first facial encoding corresponding to the specified registered user, and determining whether the person participating in the video call is the specified registered user.

Abstract: Systems and methods for verifying identifies of parties to a video conference call are disclosed. An example method includes storing a plurality of first facial encodings each associated with one or more images of a registered agent, receiving, during the video conference call, a second facial encoding associated with one or more images of a person participating in the video conference call, determining that a specified registered agent is scheduled as a party to the video conference call, comparing the second facial encoding to a selected first facial encoding associated with the specified registered agent, and determining, based at least in part on the comparing, whether or not the person is the specified registered agent.

Abstract: Systems and methods for verifying identifies of parties to a video conference call are disclosed. An example method includes storing a plurality of first facial encodings each associated with one or more images of a registered agent, receiving, during the video conference call, a second facial encoding associated with one or more images of a person participating in the video conference call, determining that a specified registered agent is scheduled as a party to the video conference call, comparing the second facial encoding to a selected first facial encoding associated with the specified registered agent, and determining, based at least in part on the comparing, whether or not the person is the specified registered agent.

Abstract: A two-layer multi-chip package (MCP) test program architecture, test program, and programming method for testing an MCP. A program implemented according to the architecture includes a global layer defining global resources and global test functions, and respective local layers associated with each of a plurality of dies in the MCP defining respective local resources and respective local test functions specific to the respective dies.

Abstract: A method including creating a mapping file and a package test program for testing an electronic package. The package comprises a device. The package test program comprises source code for a device test program for testing the device and source code from the mapping file. The device test program source code comprises a reference to a device pin identifier which identifies an associated device pin. Each identified device pin is attached to an associated package pin. Each package pin is identified by a package pin identifier. The mapping file redefines each device pin identifier to be the associated package pin identifier in the package test program. At least one instruction in the package test program created from the device test program source code is configured to attach a tester resource to one of the package pins, and to appropriately activate the tester resource.