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This paper proposes a new model-based method for transform coding of audio signals. The input signal is mapped in "perceptual" domain by linear-predictive weighting filter followed by modified discrete cosine transform (MDCT). To provide bitstream scalability, model-based bit plane coding is then applied with respect to the mean square error (MSE) criterion. We present methods to estimate the symbol probability in bit planes assuming a generalized Gaussian model for the distribution of MDCT coefficients. We compare the performance of the proposed bitstream scalable coder with stack-run coding and ITU-T G.722.1. Objective and subjective quality results are presented. The proposed coder is equivalent to or slightly worse than reference coders, but presents the nice advantage of being scalable. Performance penalty due to bitstream scalability is evident at low bitrates.