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This paper proposes a classification module for fricative consonants in telephone speech using an acoustic-phonetic feature extrapolation technique. In channel-deteriorated telephone speech, acoustic cues of fricative consonants are expected to be degraded or missing due to limited bandwidth. This paper applies an extrapolation technique to acoustic-phonetic features based on Gaussian mixture models, which uses a statistical learning of the correspondence between acoustic-phonetic features of wideband speech and the spectral characteristics of telephone bandwidth speech. Experimental results with NTIMIT database verify that feature extrapolation improves the performance of fricative classification module for all unvoiced fricatives by around 10% (relative error) compared to the performance obtained by only acoustic-phonetic features extracted from the narrowband signal.