Empirical Lower Bound on the Bitrate for the Transparent Memoryless Coding of Wideband LPC Parameters

In this letter, we determine empirical lower bounds on the bitrate required to transparently code linear predictive coding (LPC) parameters derived from wideband speech. This is achieved via extrapolation of the operating distortion-rate curve of an unconstrained vector quantizer that is trained using artificial vectors generated by a Gaussian mixture model. Memoryless coding is considered and two competing LPC parameter representations are investigated. Our results show a lower bound of 31 bits/frame when assuming high-rate linearity in the operating distortion-rate curve and 35 bits/frame for an exponential curve. We also evaluate a recent quantization scheme and compare its performance against this lower bound