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In this paper, we study the effects of different ASE noise models on the performance of turbo code (TC) decoders. A soft-decoding algorithm, the Bahl, Cocke, Jelinek, and Raviv (BCJR) decoding algorithm, is generally used in TC decoders. The BCJR algorithm is a maximum a posteriori probability (MAP) algorithm, and is very sensitive to noise statistics. The Gaussian approximation of ASE noise is widely used in the study of optical-fiber communication systems, and there exist standard TCs for additive white Gaussian noise (AWGN) channels. We show that using a MAP decoding algorithm based on the Gaussian noise assumptions, however, may significantly degrade the TC decoder performance in an optical-fiber channel with non-Gaussian ASE noise. To take full advantage of TC, accurate noise statistics in optical-fiber transmissions should be used in the MAP decoding algorithm.