1. A method of modeling a signal comprising: a) identifying a plurality of harmonic frequencies; b) identifying a plurality of harmonic magnitudes corresponding to spectral magnitudes of the signal at the plurality of harmonic frequencies; c) interpolating the plurality of harmonic magnitudes to obtain a plurality of spectral magnitudes at a set of fixed frequencies; d) inverse transforming the plurality of spectral magnitudes to obtain a pseudo auto-correlation sequence; e) calculating linear prediction coefficients from the pseudo auto-correlation sequence; f) calculating model harmonic magnitudes by sampling a spectral envelope defined by the linear prediction coefficients; g) calculating a first set of scale factors as the ratio of the harmonic magnitudes to the model harmonic magnitudes; h) interpolating the first set of scale factors to obtain a second set of scale factors at the set of fixed frequencies; i) calculating model spectral magnitudes at the set of fixed frequencies by sampling the spectral envelope defined by the linear prediction coefficients at the set of fixed frequencies; j) multiplying the model spectral magnitudes at the set of fixed frequencies by the second set of scale factors to obtain a new plurality of spectral magnitudes; k) inverse transforming the new plurality of spectral magnitudes to obtain a new pseudo auto-correlation sequence; and l) calculating new linear prediction coefficients from the new pseudo auto-correlation sequence, wherein the signal is modeled by the new linear prediction coefficients.