Abstract: A method for enhancing telephone speech signals based on Deep Convolutional Neural Network (CNN) is disclosed. The method is able to reduce the effect of acoustic distortions in daily scenarios during a telephone call. It is a single-channel, speech-oriented method with causal design and low latency. The novelty lies in the noise reduction method which, based on the classical gain method, uses a CNN to learn the Wiener estimator. Then, it computes the gain of the filter to enhance the speech power over the noise power for each time-frequency component of the signal. The selection of the Wiener gain estimator as an essential element of the method, decreases the vulnerability to estimation errors since the characteristics of this measure make it very appropriate to be estimated by deep learning approaches.

Abstract: A method for enhancing telephone speech signals based on Deep Convolutional Neural Network (CNN) is disclosed. The method is able to reduce the effect of acoustic distortions in daily scenarios during a telephone call. It is a single-channel, speech-oriented method with causal design and low latency. The novelty lies in the noise reduction method which, based on the classical gain method, uses a CNN to learn the Wiener estimator. Then, it computes the gain of the filter to enhance the speech power over the noise power for each time-frequency component of the signal. The selection of the Wiener gain estimator as an essential element of the method, decreases the vulnerability to estimation errors since the characteristics of this measure make it very appropriate to be estimated by deep learning approaches.

Abstract: System for classifying whether audio data received in a speaker recognition system is genuine or a spoof using a Gaussian classifier and method for classifying whether audio data received in a speaker recognition system is genuine or a spoof using a Gaussian classifier.

Abstract: The present invention refers to a method for verifying the identity of a speaker based on the speaker's voice comprising the steps of: a) receiving a voice utterance; b) using biometric voice data to verify that the speakers voice corresponds to the speaker the identity of which is to be verified based on the received voice utterance; and c) verifying that the received voice utterance is not falsified, preferably after having verified the speakers voice; d) accepting the speaker's identity to be verified in case that both verification steps give a positive result and not accepting the speaker's identity to be verified if any of the verification steps give a negative result. The invention further refers to a corresponding computer readable medium and a computer.

Abstract: The invention refers to a method for comparing voice utterances, the method comprising the steps: extracting a plurality of features (201) from a first voice utterance of a given text sample and extracting a plurality of features (201) from a second voice utterance of said given text sample, wherein each feature is extracted as a function of time, and wherein each feature of the second voice utterance corresponds to a feature of the first voice utterance; applying dynamic time warping (202) to one or more time dependent characteristics of the first and/or second voice utterance e.g.

Abstract: System for classifying whether audio data received in a speaker recognition system is genuine or a spoof using a Gaussian classifier and method for classifying whether audio data received in a speaker recognition system is genuine or a spoof using a Gaussian classifier.

Abstract: The invention refers to a method for comparing voice utterances, the method comprising the steps: extracting a plurality of features (201) from a first voice utterance of a given text sample and extracting a plurality of features (201) from a second voice utterance of said given text sample, wherein each feature is extracted as a function of time, and wherein each feature of the second voice utterance corresponds to a feature of the first voice utterance; applying dynamic time warping (202) to one or more time dependent characteristics of the first and/or second voice utterance e.g.

Abstract: Method and system for canceling echoes and noises in environments with variable acoustic conditions and high feedback, such as the interior of an automotive vehicle, permitting audible communication between the occupants, comprising one/several microphone/s (1) for a speech signal (5) and A/D, D/A converters, amplification and filtering means generating an electric signal (13) reproduced as an acoustic signal (7) by a speaker (3), and an echo canceller (15) using said signal (13) and an electric signal (10) from the microphone integrating the feedback of said signal (7), another speech signal (5) and noise (9) seized by the microphone (1), the system (15) being applied to eliminating said feedback, the proposed method and system providing an additional filtering of an electric output signal (11) of the canceling device (15), after treatment of said signal, comprising a time variant filter that suppresses the residual acoustic echo not cancelled by the system (15) and the noise seized by said microphone/s (1).

Abstract: Method and system for canceling echoes and noises in environments with variable acoustic conditions and high feedback, such as the interior of an automotive vehicle, permitting audible communication between the occupants, comprising one/several microphone/s (1) for a speech signal (5) and A/D, D/A converters, amplification and filtering means generating an electric signal (13) reproduced as an acoustic signal (7) by a speaker (3), and an echo canceller (15) using said signal (13) and an electric signal (10) from the microphone integrating the feedback of said signal (7), another speech signal (5) and noise (9) seized by the microphone (1), the system (15) being applied to eliminating said feedback, the proposed method and system providing an additional filtering of an electric output signal (11) of the canceling device (15), after treatment of said signal, comprising a time variant filter that suppresses the residual acoustic echo not cancelled by the system (15) and the noise seized by said microphone/s (1).