A hearing device 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 comprising o an input unit (M; M1, M2) for providing at least one electric input signal (IN; IN1, IN2) in a time-frequency representation k, t, where k and t are frequency and time indices, respectively, and k represents a frequency sub-band signal, k =1,..., K, the at least one electric input signal being representative of sound and comprising target signal components and noise components; and o a signal processor comprising ∘ an SNR estimator (SNR-EST) for providing a target signal-to-noise ratio estimate SNR(k,t) for said at least one electric input signal (IN; IN1, IN2), or a signal originating therefrom, in said time-frequency representation; ∘ an SNR-to-gain converter (SNR2G) for converting said target signal-to-noise ratio estimates SNR ( k,t) to respective gain values G ( k,t) in said time-frequency representation; and ∘ wherein the signal processor is configured to apply the gain values G ( k,t) provided by the SNR-to-gain converter (SNR2G) to the at least one electric input signal, or to a signal derived therefrom; CHARACTERIZED IN THAT said signal processor comprises a neural network comprising at least one layer defined as a gated recurrent unit, the gated recurrent unit comprising memory in the form of a hidden state vector h, and wherein an output vector o ( t) is provided by said gated recurrent unit in dependence of an input vector x ( t) and said hidden state vector h ( t -1), wherein said output o ( t) at a given time step t is stored as said hidden state h ( t) and used in the calculation of the output vector o ( t +1) in the next time step t +1, and wherein at least said SNR-to-gain converter (SNR2G) is implemented by said neural network (NN-layer, GRU, NN-layer; RNN), and wherein said at least one layer defined as a gated recurrent unit is implemented as a modified gated recurrent unit, wherein the signal processor is configured - at a given time instance t - to calculate changes Δx ( i,t) = x ( i,t) - x̂ ( i,t - 1), and Δ h ( j, t -1) = h ( j,t - 1) - ĥ ( j,t - 2) to the input vector x ( t) and to the hidden state vector h ( t -1), respectively, from one time instance, t -1, to the next, t, and where x̂ ( i,t- 1) and ĥ ( j,t - 2) are estimated values of x ( i,t- 1) and h ( j,t -2), respectively, where indices i, j refers to the i th input neuron and the j th neuron of the hidden state, respectively, where 1 ≤ i ≤ N ch,x and 1 ≤ j ≤ N ch,oh, wherein N ch,x and N ch,oh is the number of processing channels of the input vector x and the hidden state vector h, respectively, and wherein the signal processor is further configured to provide that the number of updated channels among said N ch,x and said N ch,oh processing channels of the modified gated recurrent unit for said input vector x ( t) and said hidden state vector h ( t-1), respectively, at said given time instance t is limited to a number of peak values N p,x and N p,oh, respectively, where N p.x is smaller than N ch,x, and N p,oh, is smaller than N ch,oh. o an input unit (M; M1, M2) for providing at least one electric input signal (IN; IN1, IN2) in a time-frequency representation k, t, where k and t are frequency and time indices, respectively, and k represents a frequency sub-band signal, k =1,..., K, the at least one electric input signal being representative of sound and comprising target signal components and noise components; and o a signal processor comprising ∘ an SNR estimator (SNR-EST) for providing a target signal-to-noise ratio estimate SNR(k,t) for said at least one electric input signal (IN; IN1, IN2), or a signal originating therefrom, in said time-frequency representation; ∘ an SNR-to-gain converter (SNR2G) for converting said target signal-to-noise ratio estimates SNR ( k,t) to respective gain values G ( k,t) in said time-frequency representation; and ∘ wherein the signal processor is configured to apply the gain values G ( k,t) provided by the SNR-to-gain converter (SNR2G) to the at least one electric input signal, or to a signal derived therefrom; ∘ an SNR estimator (SNR-EST) for providing a target signal-to-noise ratio estimate SNR(k,t) for said at least one electric input signal (IN; IN1, IN2), or a signal originating therefrom, in said time-frequency representation; ∘ an SNR-to-gain converter (SNR2G) for converting said target signal-to-noise ratio estimates SNR ( k,t) to respective gain values G ( k,t) in said time-frequency representation; and ∘ wherein the signal processor is configured to apply the gain values G ( k,t) provided by the SNR-to-gain converter (SNR2G) to the at least one electric input signal, or to a signal derived therefrom;