Although emotions play a major role in voice communication, the quality of their reproduction by low bit rate voice coders has never been investigated so far. This paper shows that the emotional state of a speaker can be identified automatically, with reasonable precision and accuracy, using conventional voice coding parameters (pitch, voicing, energy and LPC coefficients). It also shows that the performance of this identification degrades when these parameters are quantized, especially at lower rates (1200 bits/s). This suggests that quantization of speech parameters could be improved by targeting the faithful reproduction of important higher-level voice communication attributes such as emotions, rather than simply optimizing objective measures such as the signal-to-noise ratio, mean squared error and spectral distortion.