This paper addresses the reconstruction of missing samples in audio signals via model-based interpolation schemes. We demonstrate through examples that employing a frequency-warped version of Burg’s method is advantageous for interpolation of long duration signal gaps. Our experiments show that using frequencywarping to focus modeling on low frequencies allows reducing the order of the autoregressive models without degrading the quality of the reconstructed signal. Thus a better balance between qualitative performance and computational complexity can be achieved.