Several studies have been dedicated to the analysis and modeling of AM–FM modulations in speech and different algorithms have been proposed for the exploitation of modulations in speech applications. This paper details a statistical analysis of amplitude modulations using a multi-band AM-FM analysis framework. The aim of this study is to analyze the phonetic- and speaker-dependency of modulations in the amplitude envelope of speech resonances. The analysis focuses on the dependence of such modulations on acoustic features such as, fundamental frequency, formant proximity, phone identity, as well as, speaker identity and contextual features. The results show that the amplitude modulation index of a speech resonance is mainly a function of the speaker’s average fundamental frequency, the phone identity, and the proximity between neighboring formant resonances. The results are especially relevant for speech and speaker recognition application employing modulation features.