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 obtained from at least a first encounter participant. The audio encounter information obtained from at least the first encounter participant may be processed. A user interface may be generated displaying a plurality of layers associated with the audio encounter information obtained from at least the first encounter participant. A user input may be received from a peripheral device to navigate through each of the plurality of layers associated with the audio encounter information displayed on the user interface.

Abstract: A method, computer program product, and computing system for obtaining machine vision encounter information using one or more machine vision systems. Audio encounter information may be obtained using a plurality of audio acquisition devices of an audio recording system. The audio encounter information may be encoded using an audio codec. The encoding of the audio encounter information by the audio codec may be adapted based upon, at least in part, the machine vision encounter information.

Abstract: A method, computer program product, and computing system for generating a plurality of acoustic relative transfer functions associated with a plurality of audio acquisition devices of an audio recording system deployed in an acoustic environment. At least a pair of the plurality of acoustic relative transfer functions from time frames may be compared. A change in the acoustic environment may be detected based upon, at least in part, the comparison of the plurality of acoustic relative transfer functions from at least the pair of time frames.

Abstract: A method, computer program product, and computing system for defining a model representative of a plurality of acoustic variations to a speech signal, thus defining a plurality of time-varying spectral modifications. The plurality of time-varying spectral modifications may be applied to a reference signal using a filtering operation, thus generating a time-varying spectrally-augmented signal.

Abstract: A method, computer program product, and computing system for generating a plurality of acoustic relative transfer functions between a plurality of audio acquisition devices of an audio recording system based upon, at least in part, one or more of a predefined speech processing application and a predefined acoustic environment. An acoustic relative transfer function codebook may be generated using the plurality of acoustic relative transfer functions. One or more channels from the plurality of audio acquisition devices of the audio recording system may be encoded using the acoustic relative transfer function codebook.

Abstract: A method, computer program product, and computing system for receiving input content that may include sensitive information for processing by a machine learning model; processing the input content with the machine learning model to generate output content; processing the output content to determine if the output content includes any sensitive information; and if the output content includes any sensitive information, scrutinizing the input content to determine if the input content supports the inclusion of the sensitive information in the output content.

Abstract: A method, computer program product, and computing system for encoding audio encounter information of a reference audio acquisition device of a plurality of audio acquisition devices of an audio recording system, thus defining encoded reference audio encounter information. Location information may be estimated, via a machine vision system, for an acoustic source within an acoustic environment. One or more acoustic relative transfer functions may be selected from a plurality of acoustic relative transfer functions for the plurality of audio acquisition devices of the audio recording system based upon, at least in part, the location information. The encoded reference audio encounter information and a representation of the selected one or more acoustic relative transfer function may be transmitted.

Abstract: A method, computer program product, and computing system for obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information; and processing the encounter information to generate an encounter transcript.

Abstract: A method, computer program product, and computing system for processing, using a speech processing system, an input speech signal associated with a user. Context information for the input speech signal is determined from an external reference associated with the verbal communication using an artificial intelligence-based prediction system. The input speech signal is monitored for a predefined intervention pattern. In response to identifying the predefined intervention pattern in the input speech signal, one or more speech recommendations are generated for the user based upon, at least in part, the context using an artificial intelligence-based prediction system and the speech processing system.

Abstract: A method, computer program product, and computing system for executing a plurality of requests to process data using a trained machine learning model. An anomalous pattern of requests including at least a threshold amount of out-of-domain data is identified from the plurality of requests. A potential model inversion attack is detected based upon, at least in part, identifying the anomalous pattern of requests.

Abstract: A method, computer program product, and computing system for encoding audio encounter information of a reference audio acquisition device of a plurality of audio acquisition devices of an audio recording system, thus defining encoded reference audio encounter information. Location information may be estimated, via a machine vision system, for an acoustic source within an acoustic environment. One or more acoustic relative transfer functions may be selected from a plurality of acoustic relative transfer functions for the plurality of audio acquisition devices of the audio recording system based upon, at least in part, the location information. The encoded reference audio encounter information and a representation of the selected one or more acoustic relative transfer function may be transmitted.

Abstract: A method, computer program product, and computing system for generating a plurality of acoustic relative transfer functions for a plurality of audio acquisition devices of an audio recording system deployed in an acoustic environment. The plurality of acoustic relative transfer functions may be encoded into a first embedding of acoustic relative transfer functions and at least a second embedding of acoustic relative transfer functions. Information may be extracted from at least the first embedding of acoustic relative transfer functions.

Abstract: A method, computer program product, and computing system for determining a plurality of transfer functions for a plurality of corresponding segments from a reference recording and a suspect recording. A delta transfer function between the plurality of transfer functions of a pair of corresponding segments of the plurality of corresponding segments is determined. A recording comparison confidence score is generated for the pair of corresponding segments based upon, at least in part, the delta transfer function. The suspect recording is verified based upon, at least in part, the plurality of recording comparison confidence scores.

Abstract: A method, computer program product, and computing system for identifying a target output token associated with an output of a machine learning model. A portion of training data corresponding to the target output token is modified with a watermark feature, thus defining watermarked training data.

Abstract: A method, computer program product, and computing system for selecting a reference audio acquisition device from a plurality of audio acquisition devices of an audio recording system. Audio encounter information of the reference microphone may be encoded, thus defining encoded reference audio encounter information. A plurality of acoustic relative transfer functions between the reference microphone and the plurality of audio acquisition devices of the audio recording system may be generated. The encoded reference audio encounter information and a representation of the plurality of acoustic relative transfer functions may be transmitted.

Abstract: A method, computer program product, and computing system for processing audio information associated with a speech processing system and encoding a watermark in a non-disruptive portion of the audio information.

Abstract: A method, computer program product, and computing system for receiving, from a requesting party, a request to access data from a storage device. Identity information associated with the requesting party is determined. A bespoke identity-based watermark is generated for the requesting party. The bespoke identity-based watermark is encoded into the data. The watermarked data is provided to the requesting party.

Abstract: A method, computer program product, and computing system for synchronizing machine vision and audio is executed on a computing device and includes obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information and audio encounter information. The machine vision encounter information and the audio encounter information are temporally-aligned to produce a temporarily-aligned encounter recording.

Abstract: A method, computer program product, and computing system for receiving an input speech signal. A transcription of the input speech signal may be received. One or more sensitive content portions may be identified from the transcription of the input speech signal. The one or more sensitive content portions from the transcription of the input speech signal may be obscured, thus defining an obscured transcription of the input speech signal. An obscured speech signal may be generated based upon, at least in part, the input speech signal, the transcription of the input speech signal, and the obscured transcription of the input speech signal.

Abstract: A method, computer program product, and computing system for receiving an input speech signal. A transcription of the input speech signal may be generated via an automated speech recognition (ASR) system. One or more splitting points between one or more sensitive content portions and one or more non-sensitive content portions from the transcription may be identified. The input speech signal maybe split into the one or more sensitive content portions and the one or more non-sensitive content portions based upon, at least in part, the one or more splitting points, thus defining one or more sensitive content signals and one or more non-sensitive content signals.