Speech enhancement using a ternary-decision based filter

A new speech enhancement scheme based on a generalized Wiener filter formulation is proposed. A ternary-valued parameter is derived empirically based on the likelihood of the input signal vector being classified as speech. This parameter controls the Wiener filter coefficient in order to obtain an improved speech spectral estimate. This “ternary-decision” concept renders a logical compromise between the simple, hard, “binary speech/noise decision” filtering and the elaborate “soft-decision” filtering approaches in terms of practicality and performance. An important feature in our scheme is that we exploit the interframe spectral relationship to reinforce the assessment of the likelihood of weak speech components. This feature prevents many weak formants from being disproportionally attenuated as in most previous schemes. Other important features of our scheme include a novel speech/noise classifier and a robust noise median amplitude tracker, both of which make the estimate of noise spectrum more reliable. A preliminary evaluation of this new scheme is reported here