Abstract: A hearing device, e.g. a hearing aid, is configured to be arranged at least partly on a user's head or at least partly implanted in a user's head.

Abstract: A hearing device, e.g. a hearing aid, is configured to be worn by a user at or in an ear or to be fully or partially implanted in the head at an ear of the user. The hearing device comprises a) an input unit for providing at least one electric input signal in a time frequency representation k, m, where k and m are frequency and time indices, respectively, and k represents a frequency channel, the at least one electric input signal being representative of sound and comprising target signal components and noise components; and b) a signal processor comprising b1) an SNR estimator for providing a target signal-to-noise ratio estimate for said at least one electric input signal in said time frequency representation; and b2) an SNR-to-gain converter for converting said target signal-to-noise ratio estimate to respective gain values in said time frequency representation. The signal processor comprises a neural network, wherein the weights of the neural network have been trained with a plurality of training signals.

Abstract: A method of training an algorithm for optimizing intelligibility of speech components of a sound signal in hearing aids, headsets, etc.

Abstract: The application relates to a binaural hearing system comprising left and right hearing devices, e.g.

Abstract: A monaural intrusive speech intelligibility predictor unit comprises: first and second input units for providing time-frequency representations s(k,m) and x(k,m) of noise-free and noisy and/or processed versions of a target signal, respectively, k being a frequency bin index, k=1, 2, . . . , K, and m being a time index; first and second envelope extraction units for providing time-frequency sub-band representations of the signals sj(m) and xj(m), j being a frequency sub-band index, j=1, 2, . . .

Abstract: Signal processing methods for predicting the intelligibility of speech, e.g., in the form of an index that correlate highly with the fraction of words that an average listener (amongst a group of listeners with similar hearing profiles) would be able to understand from some speech material are proposed. Specifically, solutions to the problem of predicting the intelligibility of speech signals, which are distorted, e.g., by noise or reverberation, and which might have been passed through some signal processing device, e.g., a hearing aid are described. In summary, the disclosure present solutions to the following problems: 1. Monaural, non-intrusive intelligibility prediction of noisy/processed speech signals 2. Binaural, non-intrusive intelligibility prediction of noisy/processed speech signals 3. Monaural and binaural intelligibility enhancement of noisy speech signals.

Abstract: An intrusive binaural speech intelligibility predictor system receives a target signal comprising speech in left and right essentially noise-free and noisy and/or processed versions at left and right ears of a listener. The system comprises a) first, second, third and fourth input units for providing time-frequency representations of said left and right noise-free and noisy/processed versions of the target signal, respectively; b) first and second Equalization-Cancellation stages adapted to receive and relatively time shift and amplitude adjust the left and right noise-free and noisy/processed versions, respectively, and to provide resulting noise-free and noisy/processed signals, respectively; and c) a monaural speech intelligibility predictor unit for providing final binaural speech intelligibility predictor value SI-Measure based on said resulting noise-free and noisy/processed signals.

Abstract: The application relates to a binaural hearing system comprising left and right hearing devices, e.g.

Abstract: The application relates to a binaural hearing system comprising left and right hearing devices, e.g.

Abstract: An intrusive binaural speech intelligibility predictor system receives a target signal comprising speech in left and right essentially noise-free and noisy and/or processed versions at left and right ears of a listener. The system comprises a) first, second, third and fourth input units for providing time-frequency representations of said left and right noise-free and noisy/processed versions of the target signal, respectively; b) first and second Equalization-Cancellation stages adapted to receive and relatively time shift and amplitude adjust the left and right noise-free and noisy/processed versions, respectively, and to provide resulting noise-free and noisy/processed signals, respectively; and c) a monaural speech intelligibility predictor unit for providing final binaural speech intelligibility predictor value SI-Measure based on said resulting noise-free and noisy/processed signals.

Abstract: A monaural intrusive speech intelligibility predictor unit comprises: first and second input units for providing time-frequency representations s(k,m) and x(k,m) of noise-free and noisy and/or processed versions of a target signal, respectively, k being a frequency bin index, k=1, 2, . . . , K, and m being a time index; first and second envelope extraction units for providing time-frequency sub-band representations of the signals sj(m) and xj(m), j being a frequency sub-band index, j=1, 2, . . .

Abstract: Signal processing methods for predicting the intelligibility of speech, e.g., in the form of an index that correlate highly with the fraction of words that an average listener (amongst a group of listeners with similar hearing profiles) would be able to understand from some speech material are proposed. Specifically, solutions to the problem of predicting the intelligibility of speech signals, which are distorted, e.g., by noise or reverberation, and which might have been passed through some signal processing device, e.g., a hearing aid are described. In summary, the disclosure present solutions to the following problems: 1. Monaural, non-intrusive intelligibility prediction of noisy/processed speech signals 2. Binaural, non-intrusive intelligibility prediction of noisy/processed speech signals 3. Monaural and binaural intelligibility enhancement of noisy speech signals.

Abstract: The application relates to a binaural hearing system comprising left and right hearing devices, e.g.