Recently, there has been a renewed interest in techniques for coding of stereo and multi-channel audio signals. Stereo and multichannel audio signals evoke an auditory spatial image in a listener. Thus, in addition to pure redundancy reduction, a receiver model which considers properties of spatial hearing may be used for reducing the bitrate. This has been done in previous techniques by considering the importance of interaural level difference cues at high frequencies and by considering the binaural masking level difference when computing the masked threshold for multiple audio channels. Recently, a number of more systematic and parameterized such techniques were introduced. In this paper an overview over a technique, denoted binaural cue coding (BCC), is given. BCC represents stereo or multichannel audio signals as a single or more downmixed audio channels plus side information. The side information contains the interchannel cues inherent in the original audio signal that are relevant for the perception of the properties of the auditory spatial image. The relation between the inter-channel cues and attributes of the auditory spatial image is discussed. Other applications of BCC are discussed, such as joint-coding of independent audio signals providing flexibility at the decoder to mix arbitrary stereo, multichannel, and binaural signals.

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The human auditory system is able to focus on one speech signal and ignore other speech signals in an auditory scene where several conversations are taking place. This ability of the human auditory system is referred to as the “cocktail-party effect”. This property of human hearing is partly made possible by binaural listening. Interaural time differences (ITDs) and interaural level differences (ILDs) between the ear input signals are the two most important binaural cues for localization of sound sources, i.e. the estimation of source azimuth angles. This paper proposes an implementation of a cocktail-party processor. The proposed cocktail-party processor carries out an auditory scene analysis by estimating the binaural cues corresponding to the directions of the sources. And next, as a function of these cues, suppresses components of signals arriving from non-desired directions, by speech enhancement techniques. The performance of the proposed algorithm is assessed in terms of directionality and speech quality. The proposed algorithm improves existing cocktail-party processors since it combines low computational complexity and efficient source separation. Moreover the advantage of this cocktailparty processor over conventional beam forming is that it enables a highly directional beam over a wide frequency range by using only two microphones.

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