Novel approach to AM-FM decomposition with applications to speech and music analysis

We present a new zero-crossing based algorithm for decomposing a bandpass signal into the amplitude modulation (AM) and frequency modulation (FM) components. In this sequential algorithm, the FM component is first estimated using zero-crossing instant information in a k-nearest neighbour (k-NN) framework. The AM component is estimated by coherent demodulation using a time-varying lowpass filter that uses the estimated instantaneous frequency. Simulation results show that the proposed algorithm gives more accurate envelope and frequency estimates compared to the discrete-energy separation algorithm (DESA) which uses the Teager energy operator. Using the proposed approach on bandpass filtered speech and music, we can extract the fine-structured modulations that occur on a micro-time scale, within an analysis frame.