The performance of systems for speaker identification (SID) can be quite good with clean speech, though much lower with degraded speech. Thus it is useful to search for new features for SID, particularly features that are robust over a degraded channel. This paper investigates features that are robust over a degraded channel. This paper investigates features that are based on amplitude and frequency modulations of speech formants. Such modulations are measured using a high-resolution energy operator and related algorithms for recovering amplitude and frequency from an AM-FM signal. When these features are added to traditional features using an existing SID system with a telephone speech database, SID performance improved by as much as 15%. Energy onset time measurements that yielded improved SID performance are also discussed.