Abstract: A system may include a vehicle. The vehicle may include an array of haptic devices. The system may further include at least one processor configured to: determine a location of an object or occurrence relative to the user; based at least on the location of the object or occurrence relative to the user, select at least one haptic device of the array of haptic devices to be driven and function as a directional haptic alert to the user, wherein the directional haptic alert is indicative of a direction from the user toward the object or occurrence; and output at least one command to cause a driving of the selected at least one haptic device, wherein the driving of the selected at least one haptic device is perceivable by the user as the directional haptic alert.

Abstract: Configurable core domains of a speech processing system are described. A core domain output data format for a given command is originally configured with default content portions. When a user indicates additional content should be output for the command, the speech processing system creates a new output data format for the core domain. The new output data format is user specific and includes both default content portions as well as user preferred content portions.

Abstract: Configurable core domains of a speech processing system are described. A core domain output data format for a given command is originally configured with default content portions. When a user indicates additional content should be output for the command, the speech processing system creates a new output data format for the core domain. The new output data format is user specific and includes both default content portions as well as user preferred content portions.

Abstract: A speech processing model may be trained using pseudo tokens. Training a speech processing model with pseudo tokens may allow for training with a smaller amount of labeled training data and accordingly lower costs. A set of pseudo tokens may be determined by computing feature vectors from unlabeled training data, clustering the feature vectors, and performing token compression using the clustered feature vectors. A first speech processing model may be trained using unlabeled training data by determining sequences of pseudo tokens corresponding to the unlabeled training data. A second speech processing model may be initialized using the first speech processing model and then trained using labeled training data. The second speech processing model may then be deployed to a speech processing application.

Abstract: For any application that processes speech, improving the quality of the feature vectors may improve the quality of the speech application. The quality of feature vectors may be improved by modifying a neural network architecture for computing feature vectors to allocate computational resources where they are more effective for learning and computing the feature vectors. Contextual feature vectors may be computed from feature vectors by using a parameterized downsampling operation that decreases a vector sequence rate, processing the downsampled vectors with a neural network, and using a parameterized upsampling operation that increases a vector sequence rate. For example, parameterized downsampling may decrease a vector sequence rate by a factor of two, a neural may require fewer computational resources since it operates with a lower vector sequence rate, and parameterized upsampling may then increase the vector sequence rate by a factor of two.

Abstract: The amount of future context used in a speech processing application allows for tradeoffs between performance and the delay in providing results to users. Existing speech processing applications may be trained with a specified future context size and perform poorly when used in production with a different future context size. A speech processing application trained using a stochastic future context allows a trained neural network to be used in production with different amounts of future context. During an update step in training, a future-context size may be sampled from a probability distribution, used to mask a neural network, and compute an output of the masked neural network. The output may then be used to compute a loss value and update parameters of the neural network. The trained neural network may then be used in production with different amounts of future context to provide greater flexibility for production speech processing applications.

Abstract: Configurable core domains of a speech processing system are described. A core domain output data format for a given command is originally configured with default content portions. When a user indicates additional content should be output for the command, the speech processing system creates a new output data format for the core domain. The new output data format is user specific and includes both default content portions as well as user preferred content portions.

Abstract: Configurable core domains of a speech processing system are described. A core domain output data format for a given command is originally configured with default content portions. When a user indicates additional content should be output for the command, the speech processing system creates a new output data format for the core domain. The new output data format is user specific and includes both default content portions as well as user preferred content portions.

Abstract: A method is provided for model training to detect defective products. The method includes sampling training images of a product to (i) extract image portions therefrom made of a center patch and its context and (ii) black-out the center patch. The method further includes performing unsupervised back-propagation training of a Contextual Auto-Encoder (CAE) model using (i) the image portions with the blacked-out center patch as an input and, (ii) the center patch as a target output and, (iii) an image-based loss function, to obtain a trained CAE model. The method also includes sampling positive and negative center-patch-sized portions from the training images. The method additionally includes normalizing, using the trained CAE model, the positive and negative center-patch-sized portions.

Abstract: Techniques for synchronously outputting content by one or more devices are described. A system may receive a user command and may receive content responsive to the command from an application(s). The content may include various kinds of data (e.g., audio data, image data, video data, etc.). The system may also receive a presentation framework from the application, with the presentation framework indicating how content responsive to the input command should be synchronously output by one or more devices. The system determines one or more devices proximate to the user, determines which of the one or more devices may be used to output content indicated in the presentation framework, and causes the one or more devices to output content in a synchronous manner.

Abstract: Systems and methods for detecting and correcting defective products include capturing at least one image of a product with at least one image sensor to generate an original image of the product. An encoder encodes portions of an image extracted from the original image to generate feature space vectors. A decoder decodes the feature space vectors to reconstruct the portions of the image into reconstructed portions by predicting defect-free structural features in each of the portions according to hidden layers trained to predict defect-free products. Each of the reconstructed portions are merged into a reconstructed image of a defect-free representation of the product. The reconstructed image is communicated to a contrastor to detect anomalies indicating defects in the product.

Abstract: Systems and methods for proactively deleting applications and/or deactivating permissions granted thereto are described. A system determines a user's usage pattern of an application. The system also determines a standard usage pattern associated with the application. The standard usage pattern may be determined from application usage patterns of multiple users of the system. When the user's usage pattern deviates from the standard usage pattern, the system may cause the application to be deleted from one or more of the user's devices. The system may also deactivate user permissions associated with the application when the user's usage pattern deviates from the standard usage pattern. The system also outputs an indication to the user soliciting whether the system to re-download the application and/or reactivate the permissions.

Abstract: Techniques for synchronously outputting content by one or more devices are described. A system may receive a user command and may receive content responsive to the command from an application(s). The content may include various kinds of data (e.g., audio data, image data, video data, etc.). The system may also receive a presentation framework from the application, with the presentation framework indicating how content responsive to the input command should be synchronously output by one or more devices. The system determines one or more devices proximate to the user, determines which of the one or more devices may be used to output content indicated in the presentation framework, and causes the one or more devices to output content in a synchronous manner.

Abstract: A method is provided for model training to detect defective products. The method includes sampling training images of a product to (i) extract image portions therefrom made of a center patch and its context and (ii) black-out the center patch. The method further includes performing unsupervised back-propagation training of a Contextual Auto-Encoder (CAE) model using (i) the image portions with the blacked-out center patch as an input and, (ii) the center patch as a target output and, (iii) an image-based loss function, to obtain a trained CAE model. The method also includes sampling positive and negative center-patch-sized portions from the training images. The method additionally includes normalizing, using the trained CAE model, the positive and negative center-patch-sized portions.

Abstract: Systems and methods for diagnosing a patient condition include a medical imaging device for generating an anatomical image. A reconstructor reconstructs the anatomical image by reconstructing portions of the anatomical image to be a healthy representation of the portions and merging the portions into the anatomical image to generate a reconstructed image. A contrastor contrasts the anatomical image with the reconstructed image to generate an anomaly map indicating locations of difference between the anatomical image and the reconstructed image. An anomaly tagging device tags the locations of difference as anomalies corresponding to anatomical abnormalities in the anatomical image, and a display displays the anatomical image with tags corresponding to the anatomical abnormalities.

Abstract: Configurable core domains of a speech processing system are described. A core domain output data format for a given command is originally configured with default content portions. When a user indicates additional content should be output for the command, the speech processing system creates a new output data format for the core domain. The new output data format is user specific and includes both default content portions as well as user preferred content portions.

Abstract: Techniques for synchronously outputting content by one or more devices are described. A system may receive a user command and may receive content responsive to the command from an application(s). The content may include various kinds of data (e.g., audio data, image data, video data, etc.). The system may also receive a presentation framework from the application, with the presentation framework indicating how content responsive to the input command should be synchronously output by one or more devices. The system determines one or more devices proximate to the user, determines which of the one or more devices may be used to output content indicated in the presentation framework, and causes the one or more devices to output content in a synchronous manner.

Abstract: Configurable core domains of a speech processing system are described. A core domain output data format for a given command is originally configured with default content portions. When a user indicates additional content should be output for the command, the speech processing system creates a new output data format for the core domain. The new output data format is user specific and includes both default content portions as well as user preferred content portions.

Abstract: Systems and methods for proactively deleting applications and/or deactivating permissions granted thereto are described. A system determines a user's usage pattern of an application. The system also determines a standard usage pattern associated with the application. The standard usage pattern may be determined from application usage patterns of multiple users of the system. When the user's usage pattern deviates from the standard usage pattern, the system may cause the application to be deleted from one or more of the user's devices. The system may also deactivate user permissions associated with the application when the user's usage pattern deviates from the standard usage pattern. The system also outputs an indication to the user soliciting whether the system to re-download the application and/or reactivate the permissions.

Abstract: Systems and methods for diagnosing a patient condition include a medical imaging device for generating an anatomical image. A reconstructor reconstructs the anatomical image by reconstructing portions of the anatomical image to be a healthy representation of the portions and merging the portions into the anatomical image to generate a reconstructed image. A contrastor contrasts the anatomical image with the reconstructed image to generate an anomaly map indicating locations of difference between the anatomical image and the reconstructed image. An anomaly tagging device tags the locations of difference as anomalies corresponding to anatomical abnormalities in the anatomical image, and a display displays the anatomical image with tags corresponding to the anatomical abnormalities.