This paper presents an alternative mode selector based on neural networks to improve the low-complexity AMR WB+ standard audio coder especially at low bit rates. The AMR-WB+ audio coder is a multi-mode coder using both time-domain and frequency-domain modes. In low complexity operation, the standard encoder determines the coding mode on a frame-by-frame basis by essentially applying thresholding to parameters extracted from the input signal and using a logic which favors time-domain modes. The mode selector proposed in this paper reduces this bias, and achieves a mode decision which is closer to the full complexity encoder. This results in measurable quality improvements, in both objective and subjective assessments.
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