Abstract: A method, computer program product, and computing system for receiving audio encounter information from a first microphone system, thus defining a first audio stream. Audio encounter information may be received from a second microphone system, thus defining a second audio stream. Speech activity may be detected in one or more portions of the first audio stream, thus defining one or more speech portions of the first audio stream. Speech activity may be detected in one or more portions of the second audio stream, thus defining one or more speech portions of the second audio stream. The first audio stream and the second audio stream may be aligned based upon, at least in part, the one or more speech portions of the first audio stream and the one or more speech portions of the second audio stream.

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 audio encounter information from a microphone array. Speech activity within one or more portions of the audio encounter information may be identified based upon, at least in part, a correlation among the audio encounter information received from the microphone array. Location information for the one or more portions of the audio encounter information may be determined based upon, at least in part, the correlation among the signals received by each microphone of the microphone array. The one or more portions of the audio encounter information may be labeled with the speech activity and the location information.

Abstract: A method, computer program product, and computing system for receiving information associated with an acoustic environment. A plurality of filters may be predefined to produce a plurality of beams based upon, at least in part, the information associated with the acoustic environment. The plurality of filters may be predefined to produce a plurality of nulls based upon, at least in part, the information associated with the acoustic environment. Audio encounter information may be obtained, via one or more microphone arrays, using the plurality of beams and the plurality of nulls produced by the plurality of predefined filters.

Abstract: A method, computer program product, and computing system for receiving a speech signal from each microphone of a plurality of microphones, thus defining a plurality of signals. One or more noise signals associated with microphone self-noise may be received. One or more self-noise-based augmentations may be performed on the plurality of signals based upon, at least in part, the one or more noise signals associated with microphone self-noise, thus defining one or more self-noise-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. 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 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 generating a three-dimensional model of at least a portion of a three-dimensional space incorporating an ACI system via a video recording subsystem of an ACI calibration platform; and generating one or more audio calibration signals for receipt by an audio recording system included within the ACI system via an audio generation subsystem of the ACI calibration platform.

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 receiving feature-based voice data. One or more data augmentation characteristics may be received. One or more augmentations of the feature-based voice data may be generated, via a machine learning model, based upon, at least in part, the feature-based voice data and the one or more data augmentation characteristics.

Abstract: A method, computer program product, and computing system for receiving feature-based voice data associated with a first acoustic domain. One or more audio feature-based augmentations may be performed on at least a portion of the feature-based voice data. Performing the one or more audio feature-based augmentations may include adding one or more audio features to the at least a portion of the feature-based voice data and/or removing one or more audio features from the at least a portion of the feature-based voice data.

Abstract: A method, computer program product, and computing system for receiving feature-based voice data associated with a first acoustic domain. One or more gain-based augmentations may be performed on at least a portion of the feature-based voice data, thus defining gain-augmented feature-based voice data.

Abstract: A method, computer program product, and computing system for extracting acoustic metadata from a signal. The signal may be converted from the time domain to the feature domain, thus defining feature-based voice data associated with the signal. The feature-based voice data associated with the signal may be processed based upon, at least in part, the acoustic metadata.

Abstract: A method, computer program product, and computing system for receiving feature-based voice data associated with a first acoustic domain. One or more rate-based augmentations may be performed on at least a portion of the feature-based voice data, thus defining rate-based augmented feature-based voice data.

Abstract: A method, computer program product, and computing system for receiving feature-based voice data associated with a first acoustic domain. One or more reverberation-based augmentations may be performed on at least a portion of the feature-based voice data, thus defining reverberation-augmented feature-based voice data.

Abstract: A method, computer program product, and computing system for monitoring a plurality of encounter participants is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is processed to: associate at least a first portion of the encounter information with at least one known encounter participant, and associate at least a second portion of the encounter information with at least one unknown encounter participant.

Abstract: A computer-implemented method, computer program product, and computing system for rendering content is executed on a computing device and includes receiving a request to render content during a user encounter. If it is determined that the content includes sensitive content, a complete version of the content is rendered on a first device (wherein the complete version of the content includes the sensitive content) and a limited version of the content on a second device (wherein the limited version of the content excludes the sensitive content). A modular ACD system is configured to automate clinical documentation and includes a machine vision system configured to obtain machine vision encounter information concerning a user encounter. An audio recording system is configured to obtain audio encounter information concerning the user encounter. A compute system is configured to receive the machine vision encounter information and the audio encounter information.

Abstract: A method, computer program product, and computing system for source separation is executed on a computing device and includes obtaining encounter information of a patient encounter, wherein the encounter information includes first audio encounter information obtained from a first encounter participant and at least a second audio encounter information obtained from at least a second encounter participant. The first audio encounter information and the at least a second audio encounter information are processed to eliminate audio interference between the first audio encounter information and the at least a second audio encounter information.

Abstract: A computer-implemented method, computer program product, and computing system for monitoring a plurality of encounter participants is executed on a computing device and includes obtaining encounter information of a user encounter. The encounter information is processed to: associate at least a first portion of the encounter information with at least one known encounter participant, and associate at least a second portion of the encounter information with at least one unknown encounter participant. A computer-implemented method, computer program product, and computing system for populating records via semantic frames is executed on a computing device and includes obtaining encounter information of a user encounter. The encounter information is processed to generate an encounter transcript.

Abstract: A method, computer program product, and computer system for measuring, by a computing device, a plurality of Room Impulse Responses (RIRs) associated with a set of two or more microphones. At least a portion of the RIRs may be augmented. At least the portion of the RIRs may be converted to their respective Relative Transfer Function (RTF) representations. The RTF representations may be applied to training data to generate an acoustic model for automatic speech recognition.