Noisy Speech Recogniton Using CSCC

As the complex spectrum of the target signal is restored from signals of mutiple microphones for each of frequency points, the mel-filter bank outputs of the target signal (clean speech) are calculated by making weighted sums of restored spectrum $\tilde{S}(\omega)$ of the target signal according to the mel-scaling. They are Fourier transformed to Mel-Frequency Cepstral Coefficients (MFCCs) which are widely used as the feature vector for speech recognition.