Low Delay Robust Audio Coding by Noise Shaping, Fractional Sampling, and Source Prediction

It was recently shown that the combination of source prediction, two-times oversampling, and noise shaping, can be used to obtain a robust (multiple-description) audio coding frame- work for networks with packet loss probabilities less than 10%. Specifically, it was shown that audio signals could be encoded into two descriptions (packets), which were separately sent over a communication channel. Each description yields a desired performance by itself, and when they are combined, the performance is improved. This paper extends the previ- ous work to an arbitrary number of descriptions (packets) by using fractional oversampling and a new decoding principle. We demonstrate that, due to source aliasing, existing MSE optimized reconstruction rules from noisy sampled data, performs poorly from a perceptual point of view. A simple reconstruction rule is proposed, that improves the PEAQ objective difference grades (ODG) by more than 2 points. The proposed audio coder enables low- delay high-quality audio streaming on networks with late packet arrivals or packet losses. With a coding delay of 2.5 ms, and a total bitrate of 300 kbps, it is demonstrated that mean PEAQ ODGs around -0.65 can be obtained for 48 kHz (mono) music (pop & rock), and packet loss probabilities of 20%.