Loudness of complex time-varying sounds ? A challenge for current loudness models

The calculation of perceived loudness is an important factor in many applications such as the assessment of noise emissions. Generally, loudness of stationary sounds can be accurately predicted by existing models. For sounds with time-varying characteristics, however, there are still discrepancies between experimental data and model predictions, even with the most recent loudness models. This contribution presents a series of experiments in which loudness was measured in normal-hearing subjects with different types of realistic signals using an adaptive loudness matching procedure and categorical loudness scaling. The results of both methods indicate that loudness of speech-like signals is largely determined by the long-term spectrum, while other speech-related properties (particularly temporal modulations) play only a minor role. Loudness of speech appears to be quite robust towards even severe signal modifications, as long as the long-term spectrum is similar. In contrast, loudness of technical, strongly impulsive signals is considerably influenced by temporal modulations. For some of the signals, loudness could not be predicted by current models. Since the perceived loudness was underestimated by the models for some signals, but overestimated for other signals, a simple adjustment of the employed time constants in the temporal integration stage could not eliminate the discrepancies.