Abstract: Disclosed are a system and a method for singing expression transplantation. A singing expression transplantation method performed by a singing expression transplantation system according to an embodiment may comprise the steps of: synchronizing each of a first sound source and a second sound source, which include different pieces of voice information with regard to an identical song; modifying the pitch of the first sound source on the basis of pitch information extracted from each of the first sound source and the second sound source, which have been synchronized; and extracting volume information from each of the first sound source and the second sound source and adjusting the magnitude of the volume regarding the first sound source, the pitch of which has been modified, according to each piece of extracted volume information.

Abstract: Disclosed are a system and a method for singing expression transplantation. A singing expression transplantation method performed by a singing expression transplantation system according to an embodiment may comprise the steps of: synchronizing each of a first sound source and a second sound source, which include different pieces of voice information with regard to an identical song; modifying the pitch of the first sound source on the basis of pitch information extracted from each of the first sound source and the second sound source, which have been synchronized; and extracting volume information from each of the first sound source and the second sound source and adjusting the magnitude of the volume regarding the first sound source, the pitch of which has been modified, according to each piece of extracted volume information.

Abstract: A method for evaluating strength of an audio password by an electronic device is described. The method includes obtaining an audio signal captured by one or more microphones. The audio signal includes an audio password. The method also includes evaluating the strength of the audio password based on measuring one or more unique characteristics of the audio signal. The method further includes informing a user that the audio password is weak based on the evaluation of the strength of the audio password.

Abstract: A method for speech modeling by an electronic device is described. The method includes obtaining a real-time noise reference based on a noisy speech signal. The method also includes obtaining a real-time noise dictionary based on the real-time noise reference. The method further includes obtaining a first speech dictionary and a second speech dictionary. The method additionally includes reducing residual noise based on the real-time noise dictionary and the first speech dictionary to produce a residual noise-suppressed speech signal at a first modeling stage. The method also includes generating a reconstructed speech signal based on the residual noise-suppressed speech signal and the second speech dictionary at a second modeling stage.

Abstract: A method of selectively authorizing access includes obtaining, at an authentication device, first information corresponding to first synthetic biometric data. The method also includes obtaining, at the authentication device, first common synthetic data and second biometric data. The method further includes generating, at the authentication device, second common synthetic data based on the first information and the second biometric data. The method also includes selectively authorizing, by the authentication device, access based on a comparison of the first common synthetic data and the second common synthetic data.

Abstract: A method of selectively authorizing access includes obtaining, at an authentication device, first information corresponding to first synthetic biometric data. The method also includes obtaining, at the authentication device, first common synthetic data and second biometric data. The method further includes generating, at the authentication device, second common synthetic data based on the first information and the second biometric data. The method also includes selectively authorizing, by the authentication device, access based on a comparison of the first common synthetic data and the second common synthetic data.

Abstract: A method of selectively authorizing access includes obtaining, at an authentication device, first information corresponding to first synthetic biometric data. The method also includes obtaining, at the authentication device, first common synthetic data and second biometric data. The method further includes generating, at the authentication device, second common synthetic data based on the first information and the second biometric data. The method also includes selectively authorizing, by the authentication device, access based on a comparison of the first common synthetic data and the second common synthetic data.

Abstract: A method of selectively authorizing access includes obtaining, at an authentication device, first information corresponding to first synthetic biometric data. The method also includes obtaining, at the authentication device, first common synthetic data and second biometric data. The method further includes generating, at the authentication device, second common synthetic data based on the first information and the second biometric data. The method also includes selectively authorizing, by the authentication device, access based on a comparison of the first common synthetic data and the second common synthetic data.

Abstract: A method of selectively authorizing access includes obtaining, at an authentication device, first information corresponding to first synthetic biometric data. The method also includes obtaining, at the authentication device, first common synthetic data and second biometric data. The method further includes generating, at the authentication device, second common synthetic data based on the first information and the second biometric data. The method also includes selectively authorizing, by the authentication device, access based on a comparison of the first common synthetic data and the second common synthetic data.

Abstract: A sound mixture may be received that includes a plurality of sources. A model may be received that includes a dictionary of spectral basis vectors for the plurality of sources. A weight may be estimated for each of the plurality of sources in the sound mixture based on the model. In some examples, such weight estimation may be performed using a source separation technique without actually separating the sources.

Abstract: A method for speech modeling by an electronic device is described. The method includes obtaining a real-time noise reference based on a noisy speech signal. The method also includes obtaining a real-time noise dictionary based on the real-time noise reference. The method further includes obtaining a first speech dictionary and a second speech dictionary. The method additionally includes reducing residual noise based on the real-time noise dictionary and the first speech dictionary to produce a residual noise-suppressed speech signal at a first modeling stage. The method also includes generating a reconstructed speech signal based on the residual noise-suppressed speech signal and the second speech dictionary at a second modeling stage.

Abstract: A method for evaluating strength of an audio password by an electronic device is described. The method includes obtaining an audio signal captured by one or more microphones. The audio signal includes an audio password. The method also includes evaluating the strength of the audio password based on measuring one or more unique characteristics of the audio signal. The method further includes informing a user that the audio password is weak based on the evaluation of the strength of the audio password.

Abstract: A method for enhancing an audio signal by an electronic device is described. The method includes determining formant peaks based on an audio signal. The method also includes generating formant peak models. Generating formant peak models includes individually modeling each formant peak. The method further includes generating a global envelope based on the formant peak models.

Abstract: A method for noise characteristic dependent speech enhancement by an electronic device is described. The method includes determining a noise characteristic of input audio. Determining a noise characteristic of input audio includes determining whether noise is stationary noise and determining whether the noise is music noise. The method also includes determining a noise reference based on the noise characteristic. Determining the noise reference includes excluding a spatial noise reference from the noise reference when the noise is stationary noise and including the spatial noise reference in the noise reference when the noise is not music noise and is not stationary noise. The method further includes performing noise suppression based on the noise characteristic.

Abstract: A method for detecting voice activity by an electronic device is described. The method includes detecting near end speech based on a near end voiced speech detector and at least one single channel voice activity detector. The near end voiced speech detector is associated with a harmonic statistic based on a speech pitch histogram.

Abstract: A method for restoring a processed speech signal by an electronic device is described. The method includes obtaining at least one audio signal. The method also includes performing bin-wise voice activity detection based on the at least one audio signal. The method further includes restoring the processed speech signal based on the bin-wise voice activity detection.

Abstract: A sound mixture may be received that includes a plurality of sources. A model may be received that includes a dictionary of spectral basis vectors for the plurality of sources. A weight may be estimated for each of the plurality of sources in the sound mixture based on the model. In some examples, such weight estimation may be performed using a source separation technique without actually separating the sources.