5 accepted papers
Computational models of the auditory periphery are important tools for understanding mechanisms of normal and impaired hearing and for developing advanced speech and audio processing algorithms. However, the simulation of accurate neural representations entails a high computational effort. This prev…
Cochlear implant (CI) users suffer from limitations in music perception and thus prefer music which has a clear rhythm/beat and is played with only a few instruments. Therefore, existing music pre-processing methods aim to enhance music signals for CI users by either emphasizing preferred voices or…
An emphasis on the leading voice or melody is known to facilitate music perception in cochlear implant (CI) listeners while a competing accompaniment is perceived as disturbing. In this paper we present the extension of a monaural music complexity reduction scheme for CI users towards a binaural app…
While speech quality and intelligibility prediction methods for normal-hearing and hearing-impaired listeners have found a lot of attention as a cost-saving complement to listening tests, analogous procedures for music signals are still rare. In this paper a method is proposed for predicting percept…
Since natural acoustic signals like speech or music exhibit a highly varying temporal structure, signal enhancement and feature extraction algorithms benefit from segmentation procedures which take the underlying signal structure into account. In this paper we present a novel unsupervised segmentati…