Speech Enhancement Using Temporal Masking in the FFT Domain

Temporal masking models have not been previously applied in the Fast Fourier Transform (FFT) domain for speech enhancement applications. This paper presents a novel speech enhancement algorithm using temporal masking in the FFT domain. The proposed algorithm is suitable for the cochlear speech processor and for other speech applications. The input signal is analysed using FFT and then grouped into 22 critical bands. The noise power is estimated using a minimum statistics noise tracking algorithm. A short-term temporal masking threshold is then calculated for each critical band and a gain factor for each band is then computed. The objective and subjective evaluations show that the temporal masking model based speech enhancement scheme outperforms the traditional Wiener filtering approach in the FFT domain.