A new method for adaptive spectral complexity reduction of music signals

In this discussion paper we present a novel unsupervised segmentation procedure for music signals which relies on an explained variance criterion in the eigenspace of the constant-Q spectral domain. The procedure is used in the context of a spectral complexity reduction method which mitigates effects of cochlear hearing loss. It is compared to a segmentation based on equidistant boundaries. The results demonstrate that the proposed segmentation procedure gives an improvement in terms of signal- to-artefacts ratio in comparison to a segmentation based on equidistant boundaries

Music signal processing for the reduction of auditory distortions in hearing-impaired listeners

Ein sensorisch bedingter Hörverlust führt zu einer Reduktion der Frequenzselektivität und damit zu Klangfarben- und Tonhöhenverzerrungen. Derzeit verfügbare Hörhilfen rufen aufgrund technischer Einschränkungen zusätzliche Verzerrungen hervor. Daher äußern insbesondere Cochleaimplantat (CI) Träger ihre Unzufriedenheit über die Qualität der Musikwiedergabe. In dieser Arbeit werden deshalb auf der Grundlage von Dimensionsreduktionsverfahren Strategien zur Verringerung der spektralen Komplexität von Musiksignalen und damit zur Linderung von Effekten eines sensorisch bedingten Hörverlusts vorgeschlagen. Zusätzlich werden signalbasierte Maße entwickelt, die auditorische Verzerrungen bei prozessierten Musiksignalen quantifizieren sowie Musikqualitätsbewertungen durch CI-Träger vorhersagen. Die Ergebnisse zeigen, dass CI-Träger die durch das vorgeschlagene Verfahren prozessierten Musikstücke signifikant gegenüber den nicht verarbeiteten Musikstücken bevorzugen.Cochlear hearing loss leads to a reduction of frequency selectivity, which causes distortions of timbre and pitch. In addition, technical limitations of currently available hearing instruments cause further perceptual distortions. Therefore, especially cochlear implant (CI) listeners express their dissatisfaction with the quality of music reproduction. Hence, in this work we propose strategies for reducing the spectral complexity of music signals based on dimensionality reduction techniques which mitigate effects of cochlear hearing loss. Furthermore, we propose signal-based metrics which quantify changes of auditory distortion in processed music signals and predict music quality ratings of CI listeners. The results show that CI listeners significantly prefer music signals processed by the proposed method over the unprocessed case

Interactive evaluation of a music preprocessing scheme for Cochlear implants based on spectral complexity reduction

Music is difficult to access for the majority of CI users as the reduced dynamic range and poor spectral resolution in cochlear implants (CI), amongst others constraints, severely impair their auditory perception. The reduction of spectral complexity is therefore a promising means to facilitate music enjoyment for CI listeners. We evaluate a spectral complexity reduction method for music signals based on principal component analysis that enforces spectral sparsity, emphasizes the melody contour and attenuates interfering accompanying voices. To cover a wide range of spectral complexity reduction levels a new experimental design for listening experiments was introduced. It allows CI users to select the preferred level of spectral complexity reduction interactively and in real-time. Ten adult CI recipients with post-lingual bilateral profound sensorineural hearing loss and CI experience of at least 6 months were enrolled in the study. In eight consecutive sessions over a period of 4 weeks they were asked to choose their preferred version out of 10 different complexity settings for a total number of 16 recordings of classical western chamber music. As the experiments were performed in consecutive sessions we also studied a potential long term effect. Therefore, we investigated the hypothesis that repeated engagement with music signals of reduced spectral complexity leads to a habituation effect which allows CI users to deal with music signals of increasing complexity. Questionnaires and tests about music listening habits and musical abilities complemented these experiments. The participants significantly preferred signals with high spectral complexity reduction levels over the unprocessed versions. While the results of earlier studies comprising only two preselected complexity levels were generally confirmed, this study revealed a tendency toward a selection of even higher spectral complexity reduction levels. Therefore, spectral complexity reduction for music signals is a useful strategy to enhance music enjoyment for CI users. Although there is evidence for a habituation effect in some subjects, such an effect has not been significant in general