Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for performing speaker verification. A system configured to practice the method receives a request to verify a speaker, generates a text challenge that is unique to the request, and, in response to the request, prompts the speaker to utter the text challenge. Then the system records a dynamic image feature of the speaker as the speaker utters the text challenge, and performs speaker verification based on the dynamic image feature and the text challenge. Recording the dynamic image feature of the speaker can include recording video of the speaker while speaking the text challenge. The dynamic feature can include a movement pattern of head, lips, mouth, eyes, and/or eyebrows of the speaker. The dynamic image feature can relate to phonetic content of the speaker speaking the challenge, speech prosody, and the speaker's facial expression responding to content of the challenge.

Abstract: An interactive voice response system is provided that includes an interactive voice recognition module, an image collection module, and a data extraction module. The image collection module communicates with the voice recognition module and the user device. The extraction module communicates with the image collection module. The voice recognition module collects speech data from a user of the user device and provides an indication to the image collection module when the speech data includes complex data. The image collection module, in response to the indication, communicates with the user device in a text message. The text message includes a link that, when activated, opens a camera on the user device. The image collection module, in response to receiving an image having the complex data from the camera, communicates the image to the extraction module, which extracts the complex data from the image as textual data.

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 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 monitoring a plurality of conversations within a monitored space to generate a conversation data set; processing the conversation data set using machine learning to: define a system-directed command for an ACI system, and associate one or more conversational contexts with the system-directed command; detecting the occurrence of a specific conversational context within the monitored space, wherein the specific conversational context is included in the one or more conversational contexts associated with the system-directed command; and executing, in whole or in part, functionality associated with the system-directed command in response to detecting the occurrence of the specific conversational context without requiring the utterance of the system-directed command and/or a wake-up word/phrase.

Abstract: A method, computer program product, and computing system for receiving one or more inputs indicative of at least one of: a relative location of a speaker and a microphone array, and a relative orientation of the speaker and the microphone array. One or more reference signals may be received. A speech processing system may be trained using the one or more inputs and the one or more reference signals.

Abstract: A method, computer program product, and computing system for initiating a session within an ACI platform; receiving an authentication request from a requester; and authenticating that the requester has the authority to access the ACI platform.

Abstract: A method, computer program product, and computing system for defining 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 plurality of feature coefficients of a target domain of a reference signal, thus generating a plurality of time-varying spectrally-augmented feature coefficients of the reference signal.

Abstract: A method, computer program product, and computing system for defining a library of functional modules; enabling a user to select a plurality of functional modules from the library of functional modules; and enabling the user to visually arrange the plurality of functional modules to form a conversational application.

Abstract: Techniques for presenting alternative hypotheses for medical facts may include identifying, using at least one statistical fact extraction model, a plurality of alternative hypotheses for a medical fact to be extracted from a portion of text documenting a patient encounter. At least two of the alternative hypotheses may be selected, and the selected hypotheses may be presented to a user documenting the patient encounter.

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, 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 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: 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: 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, 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.