Motivated by theoretical and experimental evidences [e.g., in H. Teager and S. Teager, Proc. NATOASI: SpeechProductionandSpeechModeling, Bonas, France (1989)] that various nonlinear phenomena during speech production cause modulations of the airflow, AM–FM models for speech resonances and a novel efficient algorithm to estimate their parameters were proposed in [P. Maragos, J. Kaiser, and T. Quatieri, IEEE Trans. Signal Process. 41, 3024–3051 (1993)]. The algorithm uses the differential operation Ψ(x)=(ẋ)2−xẍ to detect modulations in speech signals by tracking the physical energy implicit in the particular ‘‘source’’ producing the observed acoustic resonance signal and by separating this energy into its time-varying amplitude and frequency components. In this paper experimental results are reported on using refinements of this energy separation algorithm to measure modulations in speech resonances. These results indicate that voiced speech signals, bandpass filtered around speech formants, contain significant amplitude and frequency modulations within a pitch period. These modulation features seem promising for applications to speech coding, synthesis, and recognition. Further, applying the algorithm on synthetic speech produced by conventional linear synthesizers did not yield the modulations patterns found in real speech. [P. Maragos is supported by the National Science Foundation. T. F. Quatieri is supported by the Department of the Air Force.]