Abstract: A method, computer program product, and computing system for processing a speech signal. A sensitive portion of the speech signal is identified. A pseudo-speech representation of the sensitive portion is generated using a voice converter system. Speech processing is performed on the speech signal and the pseudo-speech representation of the sensitive portion using a speech processing system.

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 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 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: There is provided a speech processing system that includes a neural encoder module. A processor that receives an audio signal; and the memory that contains instructions that control said processor to perform operations that process speech. In an implementation, a front end module can include a Neural Spatial RTF Estimator and a neural spatial and residual encoder (NSRE) configured accept as inputs a spectral encoded reference channel stream to output Neural Transfer Functions (NTFs). In another implementation, a front end module encodes and outputs a Ch1 bitstream; computes a plurality of relative transfer functions (RTFs) for an N-Channel signal and outputs an N?1 RTFs or an RTF codebook ids and computes and processes an N?1 residual stream; and a back end module comprising a neural encoder module configured to accept the RTFs and output an encoded speech signal comprising an embedding that comprises features extracted from RTFs.

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: Methods, apparatuses, and computer program products are described for presenting an interactive audio-visual presentation of transaction documents. A method can include receiving a bill associated with a payor and payee, using a textual language processor or the like to identify content fields from the bill and assign markups and/or metadata to content fields, and using the content fields, markups, and/or metadata to generate an audio-visual presentation associated with the bill. This audio-visual presentation can be presented to the payor. The payee may then interact with the audio-visual presentation, for instance by verbal, visual, manual, or textual response. A verbal language processing engine, natural language processing engine, audio-visual language processing engine, or visual-manual language processing engine can be initiated to facilitate interpretation of the payee response and generate a further audio-visual presentation.

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 receiving a speech signal from a single microphone. A sensitive speech component is identified from the speech signal. In response to identifying the sensitive speech component, a filtered speech signal is generated by removing the sensitive speech component from the speech signal. A voice style transfer of the speech signal is generated. Speech processing is performed on the filtered speech signal and the voice style transfer of the speech signal.

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 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: Methods, apparatuses, and computer program products are described for aggregating user sessions for conversational exchanges using a virtual assistant. A user device can receive conversational inputs, convert the conversational inputs into textual strings, associate, based upon semantic analysis of different portions of the textual strings, a first network and a second network, and initiate, respectively, a first and second user session with a first response module of the first network and a second response module of the second network. The portions of textual strings can be transmitted to the first and second response modules via, respectively, the first and second user sessions. Once response fragments are received from the first and second response modules, the response fragments can be combined in a semantically suitable order to form a generated response.

Abstract: Methods, apparatuses, and systems are described for artificial intelligence-based techniques for programmatically generating and integrating application programming interfaces (APIs). An example method may include, in response to receiving by one or more processors, an integration data object, processing, by the one or more processors, based at least in part on an integration machine learning model, the integration data object in order to identify one or more integration features associated with the integration data object; programmatically generating, by the one or more processors, based at least in part on the one or more integration features, an application programming interface (API) model corresponding with the integration data object; and generating, by the one or more processors, an API generation data object corresponding with the API model for execution.

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. A speaker embedding may be extracted from the input speech signal. Acoustic properties from the input speech signal may be extracted. An obscured transcription may be generated from the transcription, where the obscured transcription includes obscured representations of sensitive content from the transcription. An obscured speech signal may be generated based upon, at least in part, the extracted speaker embedding and the obscured transcription, where the obscured speech signal includes obscured representations of sensitive content from the input speech signal. The obscured speech signal may be augmented based upon, at least in part, the extracted acoustic properties.

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 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: Described are systems, apparatuses, methods, and computer program products for low-input initiation of user account-affiliated transactions. An example apparatus can comprise a processor and a memory storing program code configured to cause the apparatus to store payor information, authentication information, and account information associated with a payor; store payee information associated with payees; receive, from a payee device or a payor device, a request to initiate a payment, the request comprising information about a payor and payee as well as a payment amount; determine, based at least upon the information about the payor and payee, and the stored information, whether the payment is to a pre-approved payee or merchant with which payor has a pre-existing account; and, in an instance in which the determination is in the affirmative, initiate the payment by providing at least payor and payee information and payment amount a payment processor.