1. A noise reduction method for automatic speech recognition, including: computing a magnitude spectrum (|Y k (m)|) of a noisy speech containing a clean speech to be recognized and noise affecting the clean speech; computing a power spectrum (|Y k (m)| 2 ) of the noisy speech; computing an estimate (|{circumflex over (X)} k (m)| 2 ) of a power spectrum of the clean speech; computing an estimate (|{circumflex over (D)} k (m)| 2 ) of a power spectrum of the noise; computing an estimate ({circumflex over (ξ)} k (m)) of an a priori signal-to-noise ratio as a function of the estimate (|{circumflex over (X)} k (m)| 2 ) of the power spectrum of the clean speech and the estimate (|{circumflex over (D)} k (m)| 2 ) of the power spectrum of the noise; computing an estimate ({circumflex over (γ)} k (m)) of an a posteriori signal-to-noise ratio as a function of the power spectrum (|γ k (m)| 2 ) of the noisy speech and the estimate (|{circumflex over (D)} k (m)| 2 ) of the power spectrum of the noise; computing an attenuation gain (G k (m)) as a function of the estimate ({circumflex over (ξ)} k (m)) of the a priori signal-to-noise ratio and the estimate ({circumflex over (γ)} k (m)) of the a posteriori signal-to-noise ratio; computing an estimate (|{circumflex over (X)} k (m)|) of a magnitude spectrum of the clean speech as a function of the magnitude spectrum (|Y k (m)|) of the noisy speech and the attenuation gain (G k (m)); characterized in that computing the estimates ({circumflex over (ξ)} k (m), {circumflex over (γ)} k (m)) of the a priori and the a posteriori signal-to-noise ratios includes: computing a noise weighting factor (α(m)) for weighting the estimate (|{circumflex over (D)} k (m)| 2 ) of the power spectrum of the noise in the computation of the estimates ({circumflex over (ξ)} k (m), {circumflex over (γ)} k (m)) of the a priori and the a posteriori signal-to-noise ratios; computing a spectral flooring factor (β(m)) for flooring the estimates ({circumflex over (ξ)} k (m), {circumflex over (γ)} k (m)) of the a priori and the a posteriori signal-to-noise ratios; and computing the estimates ({circumflex over (ξ)} k (m), {circumflex over (γ)} k (m)) of the a priori and the a posteriori signal-to-noise ratios also as a function of the noise weighting factor (α(m)) and the spectral flooring factor (β(m)).