A new multicomponent AM-FM demodulation with predicting frequency boundaries and its application to formant estimation

In this paper, a method using dynamic programming to predict frequency boundaries is proposed for the joint demodulation of amplitude modulation (AM) and frequency modulation (FM) for speech signals. Because of the existence of modulations in speech signal, an algorithm called energy separation algorithm (ESA) has been developed to track the energy needed by a source to produce the speech signal, and this algorithm provides an efficient solution to separate output energy product into amplitude modulation and frequency modulation components. For multicomponent AM-FM signals like speech signals, a bank of bandpass filters or a set of individual bandpass filters, whose center frequency and critical bandwidth commonly are selected through experiential selection, is necessary to get monocomponent signals. Our experimental results provide that the bandpass filter with predicted frequency boundaries instead of experiential selection is more effective in AM-FM demodulation. Formant estimation based on this demodulating method also proves it is efficient and formant tracking algorithm is not necessary at all in the estimating procedure.