A trellis-based optimal parameter value selection for audio coding

This paper considers the problem of selecting a set of parameter values from a given parameter space, in order to perform rate-distortion optimization in the context of audio compression. Due to interdependencies between parameters, separate optimization of parameter values is inherently suboptimal, yet a straightforward brute-force joint search involves prohibitive computational complexity. This work proposes a new method for joint rate-distortion optimization, while accounting for interparameter dependencies. The optimal solution is achieved, at significantly reduced complexity as compared to a brute-force search, by employing a Viterbi search over a trellis. Two objective distortion metrics are specifically considered: the average, and the maximum noise-to-mask ratio. Subjective (AB/MOS) and objective (average/maximum noise-to-mask ratio) tests demonstrate considerable gains at low bit rates of 16 kbps per channel for a 44.1-kHz sampled audio signal using the proposed approach.