Abstract: A computing system for a plurality of classes of audio events is provided, including one or more processors configured to divide a run-time audio signal into a plurality of segments and process each segment of the run-time audio signal in a time domain to generate a normalized time domain representation of each segment. The processor is further configured to feed the normalized time domain representation of each segment to an input layer of a trained neural network. The processor is further configured to generate, by the neural network, a plurality of predicted classification scores and associated probabilities for each class of audio event contained in each segment of the run-time input audio signal. In post-processing, the processor is further configured to generate smoothed predicted classification scores, associated smoothed probabilities, and class window confidence values for each class for each of a plurality of candidate window sizes.

Abstract: One example provides a computing device comprising a touch sensor, a camera, a logic subsystem, and a storage subsystem. The storage subsystem comprises instructions executable by the logic subsystem to receive image data from the camera; determine, based on the image data, information regarding one or more of a hand of a user or a stylus held by the user; and based at least on the information regarding one or more of the hand of the user or the stylus held by the user, control operation of the touch sensor.

Abstract: A computing system for a plurality of classes of audio events is provided, including one or more processors configured to divide a run-time audio signal into a plurality of segments and process each segment of the run-time audio signal in a time domain to generate a normalized time domain representation of each segment. The processor is further configured to feed the normalized time domain representation of each segment to an input layer of a trained neural network. The processor is further configured to generate, by the neural network, a plurality of predicted classification scores and associated probabilities for each class of audio event contained in each segment of the run-time input audio signal. In post-processing, the processor is further configured to generate smoothed predicted classification scores, associated smoothed probabilities, and class window confidence values for each class for each of a plurality of candidate window sizes.

Abstract: A method for distinguishing a target, wherein the target includes one or more objects of interest possibly located among a plurality of objects. The method comprises the following stages: obtaining and processing sonar or radar raw data; tracking the objects of the plurality using the processed raw data; grouping the tracked objects by associating them into one or more groups, while hierarchically arranging the tracked objects in the groups and controllably applying prior knowledge at least about characteristic features and/or constraints of the target's class; classifying the groups to classes and determining whether any of the groups matches to the target's class.

Abstract: A system and method enable processing and displaying of test results in accordance with information and specifications provided by the client requiring such services. Skills examined by a test are identified, and skill-by-skill analysis of test results is provided. Performance within constituent skill categories are compared to applicable standards, thereby providing criterion-referenced conclusions about a student's performance within each skill category tested. Evaluation and recommendation statements are generated for students or groups of students based on their test performance and procedures for automatically generating such statements are provided. Test results are also used to identify skills in which individual students and groups have the greatest potential for growth. Test reports are produced in print and electronically using the same electronic document structures and data source files to ensure consistency between the two display mechanisms.

Abstract: A system and method enable processing and displaying of test results in accordance with information and specifications provided by the client requiring such services. Skills examined by a test are identified, and skill-by-skill analysis of test results is provided. Performance within constituent skill categories are compared to applicable standards, thereby providing criterion-referenced conclusions about a student's performance within each skill category tested. Evaluation and recommendation statements are generated for students or groups of students based on their test performance and procedures for automatically generating such statements are provided. Test results are also used to identify skills in which individual students and groups have the greatest potential for growth. Test reports are produced in print and electronically using the same electronic document structures and data source files to ensure consistency between the two display mechanisms.

Abstract: A system and method enable processing and displaying of test results in accordance with information and specifications provided by the client requiring such services. Skills examined by a test are identified, and skill-by-skill analysis of test results is provided. Performance within constituent skill categories are compared to applicable standards, thereby providing criterion-referenced conclusions about a student's performance within each skill category tested. Evaluation and recommendation statements are generated for students or groups of students based on their test performance and procedures for automatically generating such statements are provided. Test results are also used to identify skills in which individual students and groups have the greatest potential for growth. Test reports are produced in print and electronically using the same electronic document structures and data source files to ensure consistency between the two display mechanisms.