Adaptive recovery techniques for real-time audio streams

There are a number of packet-loss recovery techniques proposed for streaming audio applications. However, there are few works that are able to exploit the tradeoff between the recovery quality and the computational complexity. We develop a recovery method, called DSPWR (Double Sided Pitch Waveform Replication) which is able to tolerate a much higher packet loss rate. In essence, DSPWR is composed of several procedures devised to improve the quality of the reconstructed speech. It is noted that a more sophisticated recovery scheme that can tolerate a higher degree of packet loss in general requires a larger computational cost. In view of this, we evaluate the quality of the reconstructed speech under different packet loss rates for various receiver-based recovery methods, and compare the computational complexity among these methods. Under the acceptable speech quality whose MOS (Mean Opinion Score) is above 3.5, we develop an adaptive mechanism that can select the recovery method with the minimal complexity in accordance with different packet loss rates encountered. To conduct real experiments in the networks, we implement these recovery methods and evaluate the performance of DSPWR devised and the adaptive recovery techniques empirically. As validated by our experimental results, the adaptive mechanism is able to strike a compromise between the computational overhead and the quality of the speech desired