A low-complexity loudness estimation algorithm

Audio processing applications such as rate determination, bandwidth extension, compression, and noise reduction make use of loudness metrics. Most loudness estimation algorithms are computationally expensive and often not suitable for real time applications. In this paper, we present a low-complexity loudness estimation algorithm applicable to both steady and time-varying sounds. The model computes an estimate of the excitation pattern by simultaneously pruning the frequency components and detector locations. Comparative results indicate that the proposed algorithm performs consistently well for different types of audio signals at a reduced complexity.