Abstract In this paper, we present an extension of a recently developed AM-FM decomposition algorithm, which will be referred to as the extended adaptive Quasi-Harmonic Model (eaQHM). It was previ- ously shown that the adaptive Quasi-Harmonic Model (aQHM)  is an efficient AM-FM decomposition algorithm with applications in speech analysis. In this paper, we show that a simple exten- sion of the aQHM algorithm to include not only frequency but also amplitude adaptation results in higher performance in terms of Signal-to-Reconstruction-Error Ratio (SRER). To support our hy- pothesis, eaQHM is tested both on synthetic signals and on a subset of the ARCTIC database of speech. Overall, compared with aQHM, eaQHM improves the SRER by more than 2 dB, on average.