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This letter presents an experimental study investigating the effect of frequency sub-bands on regional accent identification (AID) and speaker identification (SID) performance on the ABI-1 corpus. The AID and SID systems are based on Gaussian mixture modeling. The SID experiments show up to 100% accuracy when using the full 11.025 kHz bandwidth. The best AID performance of 60.34% is obtained when using band-pass filtered (0.23-3.4 kHz) speech. The experiments using isolated narrow sub-bands show that the regions (0-0.77 kHz) and (3.40-11.02 kHz) are the most useful for SID, while those in the region (0.34-3.44 kHz) are best for AID. AID experiments are also performed with intersession variability compensation, which provides the biggest performance gain in the (2.23-5.25 kHz) region.