Spectral complexity reduction of music signals based on frequency-domain reduced-rank approximations: An evaluation...

Methods for spectral complexity reduction of music signals were evaluated in a listening test with cochlear implant (CI) listeners. To this end, reduced-rank approximations were computed in the constant-Q spectral domain using blind and score-informed dimensionality reduction techniques, which were compared to a procedure using a supervised source separation and remixing scheme. Previous works have shown that timbre and pitch cues are transmitted inaccurately through CIs and thus cause perceptual distortions in CI listeners. Hence, the scope of this evaluation was narrowed down to classical chamber music, which is mainly characterized by timbre and pitch and less by rhythmic cues. Suitable music pieces were selected in accordance to a statistical experimental design, which took musically relevant influential factors into account. In a blind two-alternative forced choice task, 14 CI listeners were asked to indicate a preference either for the original signals or a specific processed variant. The results exhibit a statistically significant preference rate of up to 74% for the reduced-rank approximations, whereas the source separation and remixing scheme did not provide any improvement.