Abstract: A method, computer program product, and computing system for receiving audio-based content from a user who is reviewing an image on a display screen; receiving gaze information that defines a gaze location of the user; and temporally aligning the audio-based content and the gaze information to form location-based content.

Abstract: A method, computer program product, and computing system for receiving a signal from each microphone of a plurality of microphones, thus defining a plurality of signals. One or more inter-microphone gain-based augmentations may be performed on the plurality of signals, thus defining one or more inter-microphone gain-augmented signals.

Abstract: A method, computer program product, and computing system for defining a correction factor for a biometric profile of a plurality of biometric profiles based upon, at least in part, a detection performance metric associated with the biometric profile. The biometric profile may be adjusted based upon, at least in part, the detection policy for the biometric profile.

Abstract: A method of processing speech includes: providing a first set of audio data having audio features in a first bandwidth; down-sampling the first set of audio data to a second bandwidth lower than the first bandwidth; producing, by a high frequency reconstruction network (HFRN), an estimate of audio features in the first bandwidth for the first set of audio data, based on at least the down-sampled audio data; inputting, into the HFRN, a second set of audio data having audio features in the second bandwidth; producing, by the HFRN, based on a second set of audio data having audio features in the second bandwidth, an estimate of audio features in the first bandwidth for the second set of audio data; and training a speech processing system (SPS) using the estimates of audio features in the first bandwidth for the first and second sets of audio data.

Abstract: A method, computer program product, and computing system for receiving a signal from each microphone of a plurality of microphones, thus defining a plurality of signals. One or more microphone frequency responses associated with at least one microphone may be received. One or more microphone frequency response-based augmentations may be performed on the plurality of signals based upon, at least in part, the one or more microphone frequency responses, thus defining one or more microphone frequency response-based augmented signals.

Abstract: A method, computer program product, and computing system for receiving a signal from each microphone of a plurality of microphones, thus defining a plurality of signals. Harmonic distortion associated with at least one microphone may be determined. One or more harmonic distortion-based augmentations may be performed on the plurality of signals based upon, at least in part, the harmonic distortion associated with the at least one microphone, thus defining one or more harmonic distortion-based augmented signals.

Abstract: A method, computer program product, and computing system for obtaining calibration information for a three-dimensional space incorporating an ACI system; and processing the calibration information to calibrate the ACI system.

Abstract: A method, computer program product, and computing system for obtaining, by a computing device, encounter information of a patient encounter, wherein the encounter information may include audio encounter information and video encounter information obtained from at least a first encounter participant. A report of the patient encounter may be generated based upon, at least in part, the encounter information. A relative importance of a word in the report may be determined. A portion of the video encounter information that corresponds to the word in the report may be determined. The portion of the video encounter information that corresponds to the word in the report may be stored at a first location, wherein the video encounter information may be stored at a second location remote from the first location.

Abstract: Embodiments improve speech data quality through training a neural network for de-noising audio enhancement. One such embodiment creates simulated noisy speech data from high quality speech data. In turn, training, e.g., deep normalizing flow training, is performed on a neural network using the high quality speech data and the simulated noisy speech data to train the neural network to create de-noised speech data given noisy speech data. Performing the training includes minimizing errors in the neural network according to at least one of (i) a decoding error of an Automatic Speech Recognition (ASR) system processing current de-noised speech data results generated by the neural network during the training and (ii) spectral distance between the high quality speech data and the current de-noised speech data results generated by the neural network during the training.

Abstract: A method of Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) includes: recording, by a voice CAPTCHA module, a speech spoken by a user; determining, by a voice biometric service (VBS), whether a voiceprint matching the user's speech exists; and if a voiceprint matching the user's speech exists, verifying the user as a human user by the VBS. If a voiceprint matching the user's speech does not exist, the VBS i) generates a unique voiceprint for the user based on the user's speech, and/or ii) determines whether the user's speech is at least one of a synthetically generated speech and a previously recorded audio being played back. The user can perform a guest checkout without logging into the voice CAPTCHA module, in which case the VBS compares previously used voiceprints to the user's speech.

Abstract: A method of enabling a virtual assistant (VA) serving a user to dynamically acquire contextual information regarding digital media environment accessed by a user includes: extracting, by an analysis engine, the contextual information dynamically from at least one of media content accessed by the user and webpage content accessed by the user; and injecting, by the analysis engine, the extracted contextual information into a VA memory to serve the user. The analysis engine is configured to analyze the extracted contextual information using at least one machine learning (ML) model. The extracted contextual information includes at least one of topics, intents, entities, sentiments, and products of interest. The at least one ML model includes at least one of Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), speaker diarization, sentiment analysis on media streams, and web analytics for product focus.

Abstract: A method, computer program product, and computing system for receiving information associated with an acoustic environment. Acoustic metadata associated with audio encounter information received by a first microphone system may be received. One or more speaker representations may be defined based upon, at least in part, the acoustic metadata associated with the audio encounter information and the information associated with the acoustic environment. One or more portions of the audio encounter information may be labeled with the one or more speaker representations and a speaker location within the acoustic environment.

Abstract: A method, computer program product, and computing system for receiving a signal from each microphone of a plurality of microphones, thus defining a plurality of signals. One or more inter-microphone gain-based augmentations may be performed on the plurality of signals, thus defining one or more inter-microphone gain-augmented signals.

Abstract: Disclosed herein are systems, computer-implemented methods, and tangible computer-readable storage media for speaker recognition personalization. The method recognizes speech received from a speaker interacting with a speech interface using a set of allocated resources, the set of allocated resources including bandwidth, processor time, memory, and storage. The method records metrics associated with the recognized speech, and after recording the metrics, modifies at least one of the allocated resources in the set of allocated resources commensurate with the recorded metrics. The method recognizes additional speech from the speaker using the modified set of allocated resources. Metrics can include a speech recognition confidence score, processing speed, dialog behavior, requests for repeats, negative responses to confirmations, and task completions.

Abstract: A method, computer program product, and computing system for visual diarization of an encounter is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is processed to: associate a first portion of the encounter information with a first encounter participant, and associate at least a second portion of the encounter information with at least a second encounter participant. A visual representation of the encounter information is rendered. A first visual representation of the first portion of the encounter information is rendered that is temporally-aligned with the visual representation of the encounter information. At least a second visual representation of the at least a second portion of the encounter information is rendered that is temporally-aligned with the visual representation of the encounter information.

Abstract: A method, computer program product, and computing system for receiving information associated with an acoustic environment. Acoustic metadata associated with audio encounter information received by a first microphone system may be received. One or more speaker representations may be defined based upon, at least in part, the acoustic metadata associated with the audio encounter information and the information associated with the acoustic environment. One or more portions of the audio encounter information may be labeled with the one or more speaker representations and a speaker location within the acoustic environment.

Abstract: A system and method incorporate prior knowledge into the optimization and regularization of a classification and regression model. The optimization may be a regularization process and the prior knowledge may be incorporated through adjustment of a cost function. A method of at least one processor developing a classification and regression model may be provided. The method may be implemented by at least one processor that implements classification and regression model functionality, including receiving training data and adjusting the model according to the training data; testing the classification and regression model; and employing prior knowledge during an optimization of the classification and regression model. The regularizing can include adjusting feature weights according to prior knowledge. In various embodiments, such systems and methods can be used in the processing of language inputs, e.g., speech and/or text inputs, to achieve greater interpretation accuracy.

Abstract: A method, computer program product, and computing system for proactive encounter scanning is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is proactively processed to determine if the encounter information is indicative of one or more medical conditions and to generate one or more result set. The one or more result sets are provided to the user.

Abstract: According to at least one aspect, a system for remotely controlling an application installed on a device is provided. The system includes at least one processor and at least one computer-readable storage medium storing instructions which program the at least one processor to identify a task for the application installed on the device to perform, transmit a binary short message service (SMS) message to the device including a task code associated with the identified task, receive an information request from the device responsive to the binary SMS message, and transmit task information to the device responsive to receiving the information request.

Abstract: A remote control device includes a digital audio storage device, a talk button, and an optical distance measurer. The digital audio storage device is configured to continually record an audio input for a specific amount of time. The talk button is coupled to the digital audio storage device and is configured to initiate a transmission of the audio input to a set-top box device. The optical distance measurer is coupled to the talk button and is configured to automatically measure a distance to a user in response to the talk button being pressed.