Nagathil Anil, Weihs Claus, Neumann Katrin, Martin Rainer
Institute of Communication Acoustics, Ruhr-Universität Bochum, 44780 Bochum, Germany.
Chair of Computational Statistics, Faculty of Statistics, TU Dortmund, 44221 Dortmund, Germany.
J Acoust Soc Am. 2017 Sep;142(3):1219. doi: 10.1121/1.5000484.
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.
在一项针对人工耳蜗（CI）使用者的听力测试中，对音乐信号频谱复杂度降低方法进行了评估。为此，在恒定Q谱域中使用盲法和分数告知降维技术计算降秩近似，并将其与使用监督源分离和重新混合方案的过程进行比较。先前的研究表明，音色和音高线索通过人工耳蜗传输不准确，从而在人工耳蜗使用者中造成感知失真。因此，本评估范围缩小到古典室内乐，其主要特征是音色和音高，而节奏线索较少。根据统计实验设计选择合适的音乐作品，该设计考虑了音乐相关的影响因素。在一项盲法二选一强制选择任务中，14名人工耳蜗使用者被要求指出对原始信号或特定处理变体的偏好。结果显示，降秩近似的统计显著偏好率高达74%，而源分离和重新混合方案没有带来任何改善。
