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 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 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 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 includes: providing a workstation having a playback app configured for audio playback; providing a decryption module having a decryption functionality communicatively connected to the playback app; encrypting, by a server using an encryption key associated with the decryption module, audio data; and decrypting, using the decryption module, the encrypted audio data. The decryption module having the decryption functionality is provided as part of the playback app, as part of firmware of a headphone, or as part of a phone app. The method can additionally include: i) authenticating, using a voice biometric authentication module, a transcriber; ii) enabling decryption by the decryption module only upon input of a decode PIN by the transcriber; and iii) a) modifying the audio data to spatialize speech component and noise component of the audio data at different angles using head-related transfer function (HRTF) filtering, and b) playing back the audio data binaurally.

Abstract: A method, computer program product, and computing system for obtaining one or more speech signals from a first device, thus defining one or more first device speech signals. One or more speech signals may be obtained from a second device, thus defining one or more second device speech signals. One or more acoustic relative transfer functions mapping reverberation from the one or more first device speech signals to the one or more second device speech signals may be generated. One or more augmented second device speech signals may be generated based upon, at least in part, the one or more acoustic relative transfer functions and first device training data.

Abstract: A method, computer program product, and computing system for obtaining one or more speech signals from a first device, thus defining one or more first device speech signals. One or more speech signals may be obtained from a second device, thus defining one or more second device speech signals. An acoustic relative transfer function may be selected from a plurality of acoustic relative transfer functions based upon, at least in part, the one or more first device speech signals and the one or more second device speech signals. The one or more second device speech signals may be augmented, at run-time, based upon, at least in part, the acoustic relative transfer function.

Abstract: A method, computer program product, and computing system for obtaining one or more speech signals from a first device, thus defining one or more first device speech signals. One or more speech signals may be obtained from a second device, thus defining one or more second device speech signals. A noise component model may be selected from a plurality of noise component models based upon, at least in part, the one or more first device speech signals and the one or more second device speech signals. The one or more second device speech signals may be augmented, at run-time, based upon, at least in part, the noise component model.

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 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 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 obtaining encounter information of a patient encounter; processing the encounter information to generate an encounter transcript; and processing the encounter transcript to locate one or more procedural events within the encounter transcript.

Abstract: A method, computer program product, and computing system for receiving a plurality of signals from a plurality of microphones, thus defining a plurality of channels. A weighted multichannel representation of the plurality of channels may be generated. A plurality of weights for each channel of the plurality of channels may be generated based upon, at least in part, the weighted multichannel representation of the plurality of channels. A single channel representation of the plurality of channels may be generated based upon, at least in part, the weighted multichannel representation of the plurality of channels and the plurality of weights generated for each channel of the plurality of channels.

Abstract: A method, computer program product, and computing system for: monitoring a conversation between a patient and a medical professional; identifying one or more medication recommendations for the patient based, at least in part, upon the conversation; and providing the one or more medication recommendations to the medical professional.

Abstract: A method, computer program product, and computing system for: monitoring a conversation between a plurality of participants of a telehealth session; identifying an addressable issue within the conversation; and initiating an action to mitigate the addressable issue.

Abstract: A method, computer program product, and computing system for obtaining encounter information of a patient encounter; processing the encounter information to generate an encounter transcript; and processing the encounter transcript to locate one or more procedural events within the encounter transcript.

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.