Error spreading: a perception-driven approach to handling error in continuous media streaming
IEEE/ACM Transactions on Networking (TON)
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This paper studies the design of data transformation algorithms for audio data transmitted over the Internet, with a goal of reconstructing the original signals by the receiver with little distortions in the presence of bursty loss of packets. It assumes that a single audio stream is interleaved into multiple packets, and a lost sample at the receiver is reconstructed as the interpolation of adjacent samples received. We propose a non-redundant transformation-based reconstruction algorithm that can minimize the reconstruction error for any fixed, interpolation-based reconstruction algorithm. Its basic idea is that the sender transforms the input audio stream optimally, based on the reconstruction method used at the receiver before sending the data packets. Consequently, the receiver is able to recover much better from losses of packets than without any knowledge of what the signals should be. In particular, we study our transformation algorithm based on one popular linear interpolation-based reconstruction algorithm. We found that our scheme can improve the signal-to-noise ratio (SNR) by 1 to 2 dB with very little extra computation efforts as compared to the scheme without transformation.