Adaptive Normalisation of Programme Loudness in Audiovisual Broadcasts

Abstract: Loudness is a subjective measure of how loud an audio signal is perceived. Due to commercial pressures loudness has been exploited in broadcasts to attract and reach viewers and listeners. By means of signal processing it is possible to increase the loudness of an audio signal and still meet the contemporary legislated signal levelling requirements. With an aspiration to achieve equal average loudness between all broadcasting programmes the European Broadcasting Union have issued a standard that proposes methods to quantify loudness. This thesis applies those loudness quantities and proposes an online algorithm that adaptively normalises the loudness of audiovisual broadcasts without affecting the dynamics within programmes. The main application of the algorithm is to normalise the audio in broadcasting and distributing equipment with real-time requirements. The results were derived from simulations in Matlab using commercial broadcasts. The results showed that for certain types of broadcasts the algorithm managed to reduce the variation in average programme loudness with minor effects on dynamics within programmes.