Abstract: The current document is directed to a methods and systems that use observational data collected by various devices and sensors to generate electronic-data representations of human conversations. The implementations of these methods and systems, disclosed in the current document, provide a highly extensible and generic platform for converting observational data into affect-annotated-timeline outputs that provide both a textual transcription of a conversation and a parallel set of affect annotations to the conversation. The affect-annotated-timeline outputs may be useful to researchers and developers, but also serve as inputs to any of a wide variety of downstream analytical processes and analysis systems that are, in turn, incorporated into many different types of special-purpose analysis and control systems.

Abstract: A wireless motion detection system is provided which uses a sharp band-stop and low-pass filters to reject unwanted low and high frequency components of a signal in the CSI. A gap in the frequency domain is caused by taking the absolute value of the signal when using the absolute value of channel matrix H? for motion detection. A sharp band-stop (notch) filter is used to reject any unwanted signals that have significant components in this gap. A low-pass filter is used to reject all unwanted signal after the motion highest frequency.

Abstract: A method and a system for fault diagnosis with small samples of power equipment based on virtual and real twin spaces are disclosed, which belong to the field of fault diagnosis of power equipment. The method includes: test samples containing different locations, types and severity levels of fault of power equipment are acquired to form a real physical space; a virtual mirror space is acquired by simulation according to a simulation model of the equipment to be diagnosed; the training set in the real physical space is spatially integrated with the sample set in the virtual mirror space to obtain a training sample set in the twin spaces; the training sample set in the twin spaces serves as the supplement to the training set in the real physical space, and the fault type and fault location serve as diagnostic labels to be input to the deep neural network for training.

Abstract: Systems and methods dynamically extracting n-grams for automated vocabulary updates. Text is received. An n-gram extracted from the text is matched to a canonical n-gram from a vocabulary to identify a tag for the text. An n-gram weight is computed for the n-gram extracted from the text. The n-gram weight may be computed by adjusting a term frequency of the n-gram. A relevancy score is computed for the tag using the n-gram weight and using an n-gram frequency of the canonical n-gram. The relevancy score is computed by dividing the n-gram weight by a value proportional to the n-gram frequency of the canonical n-gram. The relevancy score of the n-gram is presented.

Abstract: A tire system includes a tire-side device and a vehicle-body-side system. The tire-side device may be attached to a tire included in a vehicle. The vehicle-body-side system may be attached to a body of the vehicle. The tire-side device may output a detection signal corresponding to each of a plurality of types of detection targets. The tire-side device may perform processing of the detection signal and generate the data related to the detection target. The tire-side device may perform bidirectional communication with the vehicle-body-side system and transmit the data to the vehicle-body-side system. The vehicle-body-side system may perform bidirectional communication with the tire-side device and receive the data. The vehicle-body-side system may acquire the detection result for the detection target based on the data.

Abstract: In a sensor system for an actuator, in particular a lifting column, a force sensor is configured to detect a total force acting on an actuator part. An acceleration sensor is configured to detect an acceleration of the actuator part. Accordingly, the sensor system has a processing device, which is configured to control a drive of the actuator for moving the actuator part on a basis of the detected total force and the detected acceleration.

Abstract: An audio-visual automated speech recognition model for transcribing speech from audio-visual data includes an encoder frontend and a decoder. The encoder includes an attention mechanism configured to receive an audio track of the audio-visual data and a video portion of the audio-visual data. The video portion of the audio-visual data includes a plurality of video face tracks each associated with a face of a respective person. For each video face track of the plurality of video face tracks, the attention mechanism is configured to determine a confidence score indicating a likelihood that the face of the respective person associated with the video face track includes a speaking face of the audio track. The decoder is configured to process the audio track and the video face track of the plurality of video face tracks associated with the highest confidence score to determine a speech recognition result of the audio track.

Abstract: According to one embodiment, a monitoring apparatus includes a processing circuit. The processing circuit is configured to generate second data including a prediction value of a second sensor correlated with a first sensor from first data including a measurement value of the first sensor of which a measurement value changes suddenly in a case where the control signal changes, detect an anomaly of the system or an anomaly of at least one sensor, and make it difficult to detect the anomaly in a case where the determination signal indicates that there is a change in the control signal.

Abstract: A speech interface device is configured to receive response data from a remote speech processing system for responding to user speech. This response data may be enhanced with information such as a remote ASR result(s) and a remote NLU result(s). The response data from the remote speech processing system may include one or more cacheable status indicators associated with the NLU result(s) and/or remote directive data, which indicate whether the remote NLU result(s) and/or the remote directive data are individually cacheable. A caching component of the speech interface device allows for caching at least some of this cacheable remote speech processing information, and using the cached information locally on the speech interface device when responding to user speech in the future. This allows for responding to user speech, even when the speech interface device is unable to communicate with a remote speech processing system over a wide area network.

Abstract: The present disclosure relates to a method and a device for measuring at least one atmospheric parameter (gas, temperature). The method includes implementing steps of acquiring spectral images in the ultraviolet and/or the visible and/or the infrared range and scanning according to a tomographic principle. The spectral images are acquired using a network of optical systems such as infrared cameras, and are used to estimate the air quality and/or meteorological and/or climate parameters in a geographic area, for example an urban agglomeration.

Abstract: The embodiments of the present disclosure provide a fault diagnosis method, a method for building a fault diagnosis model, fault diagnosis equipment, electronic device, and non-transitory computer-readable storage medium. The fault diagnosis method, for diagnosing a fluid device, which includes a suction end and a discharge end, includes: obtaining a data set for diagnosing the fluid device, wherein the data set includes first characteristic data about the suction end, second characteristic data about the discharge end, and input-output difference data, and the input-output difference data represents data difference between the suction end and the discharge end; obtaining a fault diagnosis model; and determining whether the fluid device is in failure based on the fault diagnosis model and the data set.

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: A method for manufacturing system data analysis, preferably including receiving a query, determining a set of digests, and/or determining a query result. The method can optionally include merging the set of digests and/or providing the query result. A system for manufacturing system data analysis, preferably including a set of machines, a plurality of digests, and/or a set of computing systems.

Abstract: A display device including an external device interface configured to connect the display device to an external speaker; a microphone configured to receive a microphone signal; and a controller configured to: transmit an inaudible test signal to the external speaker to measure a signal delay between the external speaker and the display device, and extract a voice signal by removing an acoustic signal output from the external speaker from the microphone signal based on the measured signal delay.

Abstract: A first electronic device includes an audio outputter; a communicator configured to transmit data to and receive data from a second electronic device; a memory storing one or more instructions; and at least one processor configured to execute the one or more instructions to: obtain an audio output level of an audio that is output through the audio outputter; obtain a spacing distance between the second electronic device and the first electronic device; based on the obtained audio output level and the obtained spacing distance, obtain a voice reception notification indicating whether a voice can be accurately received by the second electronic device, and control the communicator to transmit the obtained voice reception notification to the second electronic device.

Abstract: An AI-based anomaly signatures warning recommendation system is provided. The system includes a memory having computer-readable instructions stored therein and a processor configured to execute the computer-readable instructions to access a multi-asset connected system having a plurality of production and/or process lines. Each of the plurality of production lines includes a plurality of assets. The processor is configured to access production data corresponding to a plurality of products manufactured in each of the plurality of production lines and to access sensor signal data corresponding to each of the plurality of assets. The sensor signal data is indicative of health of each of the plurality of assets. The processor is further configured to process the production data and sensor signal data for each of the plurality of assets to identify one or more anomaly instances and to perform similarity analysis on the one or more anomaly instances to identify one or more anomaly signatures.

Abstract: A method that includes obtaining a sensor reading from a sensor installed inside an underground vault and determining whether the sensor reading is indicative of an alarm state. When the sensor reading is indicative of the alarm state, the method obtains at least one new reading and determines whether the sensor reading includes sensor drift based at least in part on the at least one new reading. The alarm state is established when the sensor reading is determined not to include sensor drift. The sensor drift is removed when the sensor reading is determined to include sensor drift.

Abstract: A remote distress monitor includes a steerable microphone array, a memory, and a control system. The steerable microphone array is configured to detect audio data and generate sound data. The memory stores machine-readable instructions. The control system includes one or more processors configured to execute the machine-readable instructions. The generated sound data from the steerable microphone array is analyzed. Based at least in part on the analysis, a token associated with the audio data detected by the steerable microphone array is generated. The audio data is representative of one or more sounds associated with a distress event. The generated token is transmitted, via a communications network, to an electronic device to cause a distress response action to occur. The distress response action is associated with the distress event.

Abstract: A method for characterizing power quality events in an electrical system includes deriving electrical measurement data for at least one first virtual meter in an electrical system from (a) electrical measurement data from or derived from energy-related signals captured by at least one first IED in the electrical system, and (b) electrical measurement data from or derived from energy-related signals captured by at least one second IED in the electrical system. In embodiments, the at least one first IED is installed at a first metering point in the electrical system, the at least one second IED is installed at a second metering point in the electrical system, and the at least one first virtual meter is derived or located at a third metering point in the electrical system. The derived electrical measurement data may be used to generate or update a dynamic tolerance curve associated with the third metering point.

Abstract: A system and method for analyzing and explaining the temporal evolution of policies. The analysis of the temporal evolution of policies includes determining semantically related changes in the text of the corresponding policies over time and across the different versions of the (two or more) policy documents. An explanation of the temporal evolution of policies is provided consisting of human interpretable information relating each change to one or more events and/or contextual data. A next steps policy change is also suggested that includes a set of policy conditions based on potential future changes of similar policies and contextual data and event data. The suggestions are related to the policy relevant to the target cohort or individual. The system adapts machine learned models by receiving user feedback provided on an analysis of the correctness of the temporal evolution of policies, corresponding explanations and suggestions of the next actions.