1. A noise reduction system comprising: A) a microphone for converting sounds from its surroundings to a first observed signal in a frequency domain into a form of an electric signal, wherein the sounds comprise stationary and non-stationary noise components; B) a first discrete transform unit for converting the first observed signal to a second observed signal in a form of a power spectrum in each of a plurality of predetermined time frames; C) a second discrete transform unit for receiving as a first reference signal an output signal transmitted from an input source to an output source and converting said first reference signal to a second reference signal in a form of a power spectrum in each of the predetermined time frames; D) an echo canceller configured for applying echo cancellation in a time domain to the electric signal on a basis of the first reference signal, before said first reference signal is converted to the signal in a frequency domain; E) a noise reduction unit comprising: an adaptation unit for: obtaining estimated values of the stationary noise components included in a predetermined observed signal in the frequency domain; obtaining estimated values of the non-stationary noise components in each of the predetermined time frames corresponding to the second reference signal in a plurality of the predetermined frames preceding a current time frame; applying a first adaptive coefficient to the stationary noise components; applying a second adaptive coefficient to the non-stationary noise components; calculating the estimated values respectively of the stationary noise components and the non-stationary noise components, by use of each of the adaptive coefficients obtained by a learning phase in a noise segment wherein the observed signal does not include the non-stationary noise components, and on the basis of the reference signal in a non-noise segment where the observed signal includes the non-stationary noise components, accordingly performing the noise reduction process on the observed signal on the basis of each of the estimated values; wherein the learning phase is performed by: updating the adaptive coefficient in a way that minimizes a mean square value of a difference between the observed signal and a sum of the estimated values respectively of the stationary noise components and the non-stationary noise components in each of the predetermined frames; and repeating the obtaining of the estimated values and the updating of the adaptive coefficients, thereby learning each of the adaptive coefficients, wherein each of the adaptive coefficients to be used for calculating estimated values respectively of the stationary noise components and the non-stationary noise components is designed to be learned on a basis of the second observed signal and the second reference signal in the frequency domain at a same time; wherein each time the learning phase is performed, both of the adaptive coefficients are sequentially updated; a first multiplication unit for multiplying the estimated value of the stationary noise components by a first subtraction weight; wherein the noise reduction unit further comprises: a second multiplication unit for multiplying the estimated value of the non-stationary noise components by a second subtraction weight; and a flooring unit for outputting a power spectrum used when a speech recognition process is applied to speech.