The parameters of sigma-delta audio DAC depend mainly on digital sigma-delta modulator's features, especially on its noise transfer function (NTF). Many methods of design and optimization of the loop filter's coefficients in sigma-delta modulators have been proposed so far. These methods enable the designer to get suitable noise transfer functions for specific application. This paper reviews NTF design and optimization methods which are particularly useful in audio applications.

The aim of the study was to investigate how the time structure of a road-traffic affects the noise annoyance judgment. In a psychoacoustic experiment, the listeners judged noise annoyance of four road-traffic noise scenarios with identical numbers of vehicles and LAeq, T value but different time structure of a road traffic. The traffic structure varied from even to highly clustered across different scenarios. The scenarios were created in the laboratory from a large set of a single vehicle pass-by recordings. The scenarios were additionally filtered with filters corresponding to a typical window transfer function to simulate the situation inside the building. The experimental results showed that there is a significant difference in annoyance judgment for different traffic structures with the same LAeq, T value. The highest annoyance ratings were obtained for even traffic distribution and the most clustered distribution resulted in the lowest annoyance rating. These results correlated well with the averaged loudness, whereas the percentile loudness (N5) and level (L5) predict the opposite results.

The present study was carried out to determine whether recorded musical tones played at various pitches on a clarinet, a flute, an oboe, and a trumpet are perceived as being equal in loudness when presented to listeners at the same A-weighted level. This psychophysical investigation showed systematic effects of both instrument type and pitch that could be related to spectral properties of the sounds under consideration. Level adjustments that were needed to equalize loudness well exceeded typical values of JNDs for signal level, thus confirming the insufficiency of A-weighting as a loudness predictor for musical sounds. Consequently, the use of elaborate computational prediction is stressed, in view of the necessity for thorough investigation of factors affecting the perception of loudness of musical sounds.