Abstract: A hearing aid comprises a BTE-part adapted for being located behind an ear (ear) of a user, and comprising a) a multitude M of microphones, which—when located behind the ear of the user—are characterized by respective transfer functions, HBTEi(?, ?, r, k), representative of propagation of sound from sound sources S to the respective microphones b) a memory unit comprising complex, frequency dependent constants Wi(k)?, i=1, . . . , M, c) a beamformer filtering unit for providing a beamformed signal Y as a weighted combination of the microphone signals using said complex, frequency dependent constants The frequency dependent constants are determined to provide a resulting transfer function Hpinna(?, ?, r, k)=?i=1MWi(k)·HBTEi(?, ?, r, k), so that a difference between the resulting transfer function Hpinna(?, ?, r, k) and a transfer function HITE(?, ?, r, k) of a microphone located close to or in the ear canal fulfils a predefined criterion.

Abstract: An audio processing device comprises a) at least one input unit for providing a time-frequency representation Y(k,n) of an electric input signal representing sound consisting of target speech and noise signal components, where k and n are frequency band and time frame indices, respectively, b) a noise reduction system configured to b1) determine a first signal to noise ratio estimate ?(k,n) of said electric input signal, and to b2) determine a second signal to noise signal ratio estimate ?(k,n) of said electric input signal from said first signal to noise ratio estimate ?(k,n) based on a recursive algorithm providing non-linear smoothing, and wherein a determination of said one or more bias and/or smoothing parameters comprises the use of supervised learning, e.g. one or more neural networks. The invention may be used in audio processing devices, such as hearing aids, headsets, ear phones, active ear protection systems, handsfree telephone systems, mobile telephones, etc.

Abstract: An audio processing device comprises a) at least one input unit for providing a time-frequency representation Y(k,n) of an electric input signal representing sound consisting of target speech and noise signal components, where k and n are frequency band and time frame indices, respectively, b) a noise reduction system configured to: determine a first signal to noise ratio estimate ?(k,n) of said electric input signal, and determine a second signal to noise signal ratio estimate ?(k,n) of said electric input signal from said first signal to noise ratio estimate ?(k,n) based on a recursive algorithm providing non-linear smoothing, and wherein parameters of said smoothing are determined in dependence of the first and/or the second signal to noise ratio estimates corresponding to a multitude of frequency band indices. The invention may be used in hearing aids, headsets, ear phones, active ear protection systems, handsfree telephone systems, mobile telephones, etc.

Abstract: A hearing aid comprises a) first and second microphones b) an adaptive beamformer filtering unit comprising, b1) a memory comprising a first and second sets of complex frequency dependent weighting parameters representing a first and second beam patterns, b3) an adaptive beamformer processing unit providing an adaptation parameter ?opt(k) representing an adaptive beam pattern, b4) a memory comprising a fixed adaptation parameter ?fix(k) representing a third, fixed beam pattern, b5) a mixing unit providing a resulting complex, frequency dependent adaptation parameter ?mix(k) as a combination of said fixed and adaptively determined frequency dependent adaptation parameters ?fix(k) and ?opt(k), respectively, and b6) a resulting beamformer (Y) for providing a resulting beamformed signal YBF based on first and second microphone signals, said first and second sets of complex frequency dependent weighting parameters, and said resulting complex, frequency dependent adaptation parameter ?mix(k).

Abstract: A hearing aid comprises a BTE-part adapted for being located behind an ear (ear) of a user, and comprising a) a multitude M of microphones, which—when located behind the ear of the user—are characterized by respective transfer functions, HBTEi(?, ?, r, k), representative of propagation of sound from sound sources S to the respective microphones b) a memory unit comprising complex, frequency dependent constants Wi(k)?, i?1, . . . , M, c) a beamformer filtering unit for providing a beamformed signal Y as a weighted combination of the microphone signals using said complex, frequency dependent constants The frequency dependent constants are determined to provide a resulting transfer function Hpinna(?, ?, r, k)=?i=1MWi(k)·HBTEi(?, ?, r, k), so that a difference between the resulting transfer function Hpinna(?, ?, r, k) and a transfer function HITE(?, ?, r, k) of a microphone located close to or in the ear canal fulfils a predefined criterion.

Abstract: An audio processing device comprises a) at least one input unit for providing a time-frequency representation Y(k,n) of an electric input signal representing sound consisting of target speech and noise signal components, where k and n are frequency band and time frame indices, respectively, b) a noise reduction system configured to: determine a first signal to noise ratio estimate ?(k,n) of said electric input signal, and determine a second signal to noise signal ratio estimate ?(k,n) of said electric input signal from said first signal to noise ratio estimate ?(k,n) based on a recursive algorithm providing non-linear smoothing, and wherein parameters of said smoothing are determined in dependence of the first and/or the second signal to noise ratio estimates corresponding to a multitude of frequency band indices. The invention may be used in hearing aids, headsets, ear phones, active ear protection systems, handsfree telephone systems, mobile telephones, etc.

Abstract: A hearing aid comprises a BTE-part adapted for being located behind an ear (ear) of a user, and comprising a) a multitude M of microphones, which—when located behind the ear of the user—are characterized by respective transfer functions, HBTEi(?, ?, r, k), representative of propagation of sound from sound sources S to the respective microphones b) a memory unit comprising complex, frequency dependent constants Wi(k)?, i=1, . . . , M, c) a beamformer filtering unit for providing a beamformed signal Y as a weighted combination of the microphone signals using said complex, frequency dependent constants The frequency dependent constants are determined to provide a resulting transfer function Hpinna(?,?,r,k)=?i=1MWi(k)·HBTEi(?,?,r,k), so that a difference between the resulting transfer function Hpinna(?, ?, r, k) and a transfer function HITE(?, ?, r, k) of a microphone located close to or in the ear canal fulfills a predefined criterion.

Abstract: An audio processing device comprises a) at least one input unit for providing time-frequency representation Y(k,n) of an electric input signal representing sound consisting of target speech and noise signal components, where k and n are frequency band and time frame indices, respectively, b) a noise detection and/or reduction system configured to b1) determine an a posteriori signal to noise ratio estimate ?(k,n) of said electric input signal, and to b2) determine an a priori target signal to noise signal ratio estimate ?(k,n) of said electric input signal from said a posteriori signal to noise ratio estimate ?(k,n) based on a recursive decision directed algorithm. The application further relates to a method of of estimating an a priori signal to noise ratio. The invention may e.g. be used for the hearing aids, headsets, ear phones, active ear protection systems, handsfree telephone systems, mobile telephones, etc.

Abstract: A hearing aid comprises a) first and second microphones b) an adaptive beamformer filtering unit comprising, b1) a memory comprising a first and second sets of complex frequency dependent weighting parameters representing a first and second beam patterns, b3) an adaptive beamformer processing unit providing an adaptation parameter ?opt(k) representing an adaptive beam pattern, b4) a memory comprising a fixed adaptation parameter ?fix(k) representing a third, fixed beam pattern, b5) a mixing unit providing a resulting complex, frequency dependent adaptation parameter ?mix(k) as a combination of said fixed and adaptively determined frequency dependent adaptation parameters ?fix(k) and ?opt(k), respectively, and b6) a resulting beamformer (Y) for providing a resulting beamformed signal YBF based on first and second microphone signals, said first and second sets of complex frequency dependent weighting parameters, and said resulting complex, frequency dependent adaptation parameter ?mix(k).

Abstract: A hearing aid comprises a) first and second microphones b) an adaptive beamformer filtering unit comprising, b1) a first and second memories comprising a first and second sets of complex frequency dependent weighting parameters representing a first and second beam patterns, where said first and second sets of weighting parameters are predetermined initial values or values updated during operation of the hearing aid, b3) an adaptive beamformer processing unit providing an adaptation parameter ?opt(k) representing an adaptive beam pattern configured to attenuate unwanted noise under the constraint that sound from a target direction is essentially unaltered, b4) a third memory comprising a fixed adaptation parameter ?fix(k) representing a third, fixed beam pattern, b5) a mixing unit providing a resulting complex, frequency dependent adaptation parameter ?mix(k) as a combination of said fixed and adaptively determined frequency dependent adaptation parameters ?fix(k) and ?opt(k), respectively, and b6) a resulting

Abstract: An audio processing device comprises a) at least one input unit for providing time-frequency representation Y(k,n) of an electric input signal representing sound consisting of target speech and noise signal components, where k and n are frequency band and time frame indices, respectively, b) a noise detection and/or reduction system configured to b1) determine an a posteriori signal to noise ratio estimate ?(k,n) of said electric input signal, and to b2) determine an a priori target signal to noise signal ratio estimate ?(k,n) of said electric input signal from said a posteriori signal to noise ratio estimate ?(k,n) based on a recursive decision directed algorithm. The application further relates to a method of of estimating an a priori signal to noise ratio. The invention may e.g. be used for the hearing aids, headsets, ear phones, active ear protection systems, handsfree telephone systems, mobile telephones, etc. (Fig.

Abstract: A body worn hearing system comprises a hearing device, e.g. a hearing aid, and a separate microphone unit for picking up a voice of the user. The hearing device comprises a forward path comprising an input unit for providing an electric input signal representative of sound in the environment, a signal processing unit for providing a processed signal, and an output unit for generating stimuli perceivable as sound when presented to the user based on said processed signal. The microphone unit comprises a multitude M of microphones, and a multi-input noise reduction system for providing an estimate ? of a target signal s comprising the user's voice, and comprising a multi-input beamformer filtering unit operationally coupled to said multitude of microphones. The hearing device and the microphone unit are configured to receive and transmit an audio signal from/to a communication device, respectively, and for establishing a communication link between them for exchanging information.

Abstract: An audio processing device comprises a) at least one input unit for providing time-frequency representation Y(k,n) of an electric input signal representing sound consisting of target speech and noise signal components, where k and n are frequency band and time frame indices, respectively, b) a noise detection and/or reduction system configured to b1) determine an a posteriori signal to noise ratio estimate ?(k,n) of said electric input signal, and to b2) determine an a priori target signal to noise signal ratio estimate ?(k,n) of said electric input signal from said a posteriori signal to noise ratio estimate ?(k,n) based on a recursive decision directed algorithm. The application further relates to a method of of estimating an a priori signal to noise ratio. The invention may e.g. be used for the hearing aids, headsets, ear phones, active ear protection systems, handsfree telephone systems, mobile telephones, etc. (Fig.

Abstract: A hearing aid comprises a BTE-part adapted for being located behind an ear (ear) of a user, and comprising a) a multitude M of microphones, which—when located behind the ear of the user—are characterized by respective transfer functions, HBTEi(?, ?, r, k), representative of propagation of sound from sound sources S to the respective microphones b) a memory unit comprising complex, frequency dependent constants Wi(k)?, i=1, . . . , M, c) a beamformer filtering unit for providing a beamformed signal Y as a weighted combination of the microphone signals using said complex, frequency dependent constants The frequency dependent constants are determined to provide a resulting transfer function Hpinna(?, ?, r, k)=?i=1M Wi(k)·HBTEi(?, ?, r, k), so that a difference between the resulting transfer function Hpinna(?, ?, r, k) and a transfer function HITE(?, ?, r, k) of a microphone located close to or in the ear canal fulfils a predefined criterion.

Abstract: A hearing aid comprises a) first and second microphones b) an adaptive beamformer filtering unit comprising, b1) a first and second memories comprising a first and second sets of complex frequency dependent weighting parameters representing a first and second beam patterns, where said first and second sets of weighting parameters are predetermined initial values or values updated during operation of the hearing aid, b3) an adaptive beamformer processing unit providing an adaptation parameter ?opt(k) representing an adaptive beam pattern configured to attenuate unwanted noise under the constraint that sound from a target direction is essentially unaltered, b4) a third memory comprising a fixed adaptation parameter ?fix(k) representing a third, fixed beam pattern, b5) a mixing unit providing a resulting complex, frequency dependent adaptation parameter ?mix(k) as a combination of said fixed and adaptively determined frequency dependent adaptation parameters ?fix(k) and ?opt(k), respectively, and b6) a resulting