Spectral envelope reconstruction via IGF for audio transform coding

In low-bitrate audio coding, modern coders often rely on efficient parametric techniques to enhance the performance of the waveform preserving transform coder core. While the latter features well-known perceptually adapted quantization of spectral coefficients, parametric techniques reconstruct the signal parts that have been quantized to zero by the encoder to meet the low-bitrate constraint. Large numbers of zeroed spectral values and especially consecutive zeros constituting gaps often lead to audible artifacts at the decoder. To avoid such artifacts the new 3GPP Enhanced Voice Services (EVS) coding standard utilizes noise filling and intelligent gap filling (IGF) techniques, guided by spectral envelope information. In this paper the underlying considerations of the parametric energy adjustment and transmission in EVS and its relation to noise filling, IGF, and tonality preservation are presented. It is further shown that complex-valued IGF envelope calculation in the encoder improves the temporal energy stability of some signals while retaining real-valued decoder-side processing.