Abstract: A device includes a neural network and a sample generator. The neural network is configured to process one or more neural network inputs to generate a joint probability distribution. The one or more neural network inputs include at least first previous sample data and second previous sample data associated with at least one previous data sample of a sequence of data samples. The sample generator is configured to generate first sample data and second sample data based on the joint probability distribution. The first sample data and the second sample data are associated with at least one data sample of the sequence of data samples.

Abstract: An example method of automated selection of audio asset synthesizing pipelines includes: receiving an audio stream comprising human speech; determining one or more features of the audio stream; selecting, based on the one or more features of the audio stream, an audio asset synthesizing pipeline; training, using the audio stream, one or more audio asset synthesizing models implementing respective stages of the selected audio asset synthesizing pipeline; and responsive to determining that a quality metric of the audio asset synthesizing pipeline satisfies a predetermined quality condition, synthesizing one or more audio assets by the selected audio asset synthesizing pipeline.

Abstract: Systems and techniques for updating floor plans for use by autonomous mobile devices. The techniques include accessing a first floor plan with associated spatial metadata. An updated occupancy map is received with additional geographic updates over the first floor plan. A transformation of the first floor plan is determined to match the new occupancy map. The spatial data and the first floor plan are transformed and the transformed spatial metadata is associated with the new occupancy map to form a second floor plan.

Abstract: Apparatus, systems and methods for providing a four-part, virtual reality (VR) customer service interaction between a customer service avatar operating on a VR platform and a customer using both a mobile device and a VR device are provided. Methods may include activating a VR session between the customer service avatar and the customer. Methods may include validating the VR session between the customer service avatar and the customer. Methods may include processing a co-browsing VR session request. Methods may include initiating the VR session between the customer service avatar and the customer.

Abstract: Apparatus, systems and methods for providing a four-part, virtual reality (VR) customer service interaction between a customer service avatar operating on a VR platform and a customer using both a mobile device and a VR device are provided. Methods may include activating a VR session between the customer service avatar and the customer. Methods may include validating the VR session between the customer service avatar and the customer. Methods may include processing a co-browsing VR session request. Methods may include initiating the VR session between the customer service avatar and the customer.

Abstract: Method and system for providing ground truth dataset and use thereof for improving data correctness. Datasets comprising data elements are received from different sources, each data element including an identifier and at least one attribute value associated therewith. Data correctness values are determined for the attribute values, each associated with a probability that an attribute value is correct. Data element with single data correctness value is added to the ground truth dataset for each attribute value for each identifier with which a respective attribute value is associated based on the determined data correctness values for the attribute values, whereby the data correctness values in the ground truth dataset define probability distributions of data correctness for the attribute values. Data correctness values for attribute values of data elements of a new dataset can be determined based on overlapping data compared in the ground truth dataset and the new dataset.

Abstract: An example method of automated selection of audio asset synthesizing pipelines includes: receiving an audio stream comprising human speech; determining one or more features of the audio stream; selecting, based on the one or more features of the audio stream, an audio asset synthesizing pipeline; training, using the audio stream, one or more audio asset synthesizing models implementing respective stages of the selected audio asset synthesizing pipeline; and responsive to determining that a quality metric of the audio asset synthesizing pipeline satisfies a predetermined quality condition, synthesizing one or more audio assets by the selected audio asset synthesizing pipeline.

Abstract: Systems and methods for translation of a digital document to an equivalent interactive User Interface (UI), receive the digital document containing content; detect a selection and placement of a plurality of form fields, based at least in part on the content; construct a UI template and corresponding object graph, based at least in part on the selection and placement of each of the plurality of form fields; wherein the UI template represents the content of the digital document according to a predefined document schema; and wherein the object graph is defined by one or more dependencies and one or more validations associated with the selection and placement of each of the plurality of form fields; parse the UI template; and render the UI template as an interactive UI for distribution to an end user based at least in part on a predefined rendering library.

Abstract: An example method of automated selection of audio asset synthesizing pipelines includes: receiving an audio stream comprising human speech; determining one or more features of the audio stream; selecting, based on the one or more features of the audio stream, an audio asset synthesizing pipeline; training, using the audio stream, one or more audio asset synthesizing models implementing respective stages of the selected audio asset synthesizing pipeline; and responsive to determining that a quality metric of the audio asset synthesizing pipeline satisfies a predetermined quality condition, synthesizing one or more audio assets by the selected audio asset synthesizing pipeline.

Abstract: Systems and methods for translation of a digital document to an equivalent interactive User Interface (UI), receive the digital document containing content; detect a selection and placement of a plurality of form fields, based at least in part on the content; construct a UI template and corresponding object graph, based at least in part on the selection and placement of each of the plurality of form fields; wherein the UI template represents the content of the digital document according to a predefined document schema; and wherein the object graph is defined by one or more dependencies and one or more validations associated with the selection and placement of each of the plurality of form fields; parse the UI template; and render the UI template as an interactive UI for distribution to an end user based at least in part on a predefined rendering library.

Abstract: An example method of automated selection of audio asset synthesizing pipelines includes: receiving an audio stream comprising human speech; determining one or more features of the audio stream; selecting, based on the one or more features of the audio stream, an audio asset synthesizing pipeline; training, using the audio stream, one or more audio asset synthesizing models implementing respective stages of the selected audio asset synthesizing pipeline; and responsive to determining that a quality metric of the audio asset synthesizing pipeline satisfies a predetermined quality condition, synthesizing one or more audio assets by the selected audio asset synthesizing pipeline.

Abstract: The present invention relates to providing a ground truth dataset and optimizing data correctness using the ground truth dataset. A plurality of datasets is received from different data sources. The datasets comprise a plurality of data elements. Each data element includes an identifier and at least one attribute value associated with the identifier. Data correctness values are determined for the attribute values. A data correctness value is associated with a probability that an attribute value is correct. A data element with a single data correctness value is added to the ground truth dataset for each attribute value for each identifier with which a respective attribute value is associated based on the determined data correctness values for the attribute values such that the data correctness values in the ground truth dataset define probability distributions of data correctness for the attribute values.

Abstract: Systems presented herein may automatically and dynamically modify a video game being played by a user based at least in part on a determined or predicted emotional state of a user. Using one or more machine learning algorithms, a parameter function can be generated that uses sensory and/or biometric data obtained by monitoring a user playing a video game. Based on the sensory and/or biometric data, an emotional state of the user can be predicted. For example, it can be determined whether a user is likely to be bored, happy, or frightened while playing the video game. Based at least in part on the determination of the user's emotional state, the video game can be modified to improve positive feelings and reduce negative feelings occurring in response to the video game.

Abstract: A system can manage distribution of computing jobs among a plurality of third-party network or cloud computing providers to maximize utilization of available computing resources purchased or otherwise obtained by an entity. The system can determine a dependency relationship between jobs and distribute the jobs among the network computing providers based at least in part on the dependency relationship between the jobs. Moreover, the system can use machine learning algorithms to generate one or more prediction algorithms to predict future computing resource usage demands for performing a set of scheduled and unscheduled jobs.

Abstract: Systems presented herein may automatically and dynamically modify a video game being played by a user based at least in part on a determined or predicted emotional state of a user. Using one or more machine learning algorithms, a parameter function can be generated that uses sensory and/or biometric data obtained by monitoring a user playing a video game. Based on the sensory and/or biometric data, an emotional state of the user can be predicted. For example, it can be determined whether a user is likely to be bored, happy, or frightened while playing the video game. Based at least in part on the determination of the user's emotional state, the video game can be modified to improve positive feelings and reduce negative feelings occurring in response to the video game.

Abstract: A technique to link an audio enabled device with a speech driven application without specifying the specific ones of the audio enabled device-independent, speech driven application-independent, and speech application platform independent parameters. In one example embodiment, this is accomplished by using voice framework that receives and transmits digitized speech audio without specifying the specific ones of the audio enabled device-independent and speech application platform-independent parameters. The voice framework then converts the received digital speech audio to computer readable text. Further, the voice framework receives and transmits the computer readable text to the speech driven application without specifying the specific ones of the speech driven application-independent and speech application platform-independent parameters. The voice framework then converts the computer readable text to the digital speech audio.