AM-FM based filter bank analysis for estimation of spectro-temporal envelopes and its application for speaker recognition in noisy reverberant environments

In this paper, a new AM-FM based filter bank analysis for the estimation of spectro-temporal envelope (STE) of speech signals is proposed. The filter bank is simulated by filtering a frequency translated signal using a single resonator centered around the Nyquist frequency. The proposed design of using a single fixed resonator provides distinct advantages over the traditional methods of filter bank design. First, it provides a simple IIR filter with a smooth frequency response with no ripples. Second, the bandwidth of the resonator can be easily controlled by the multiplicity of poles and their proximity to the unit circle on the z-plane. Third, the resonator fixed at the highest possible center frequency provides the best separation between the AM and FM components of the filtered signal. Speaker recognition experiments on noisy and reverberant speech with short test segments show that the proposed AM-FM based filter bank analysis for STE estimation provides consistent improvement over a recently proposed discrete cosine transform based filter bank approach.