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: An acoustic environment profile estimation is provided for automatic speech recognition (ASR) to compensate for the acoustic behavior of an environment in which audio is collected. Examples receive an audio signal and extract spectral features and modulation features. Extracting spectral features involves determining Mel filter bank (MFB) coefficients, and extracting modulation features involves applying Fourier transforms. The spectral features and modulation features are combined, and an acoustic environment profile estimate is extracted and provided as an input to the ASR. In some examples, the acoustic environment profile estimate is realized as acoustic environment parameters, whereas in some other examples, the acoustic environment profile estimate is realized as an acoustic embedding vector.

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.