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While the problem of estimating the amplitudes of sinusoidal components in signals, given an estimation of their frequencies, is linear and tractable, it is biased due to the unavoidable, in practice, errors in the estimation of frequencies. These errors are of great concern for processing signals with many sinusoidal like components as is the case of speech and audio. In this letter, we suggest using a time-varying sinusoidal representation which is able to iteratively correct frequency estimation errors. Then the corresponding amplitudes are computed through Least Squares. Experiments conducted on synthetic and speech signals show the suggested model's effectiveness in correcting frequency estimation errors and robustness in additive noise conditions.