发表机构
New York University（纽约大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究探讨双耳音乐源分离，通过感知研究评估客观空间失真指标与人类感知的关联，发现现有指标评估双耳音乐任务缺乏可靠性，ITD估计敏感，两种替代方法有稳健性和准确性的权衡，强调需设计新指标。
AI 中文摘要
尽管沉浸式音频越来越受欢迎，但双耳音乐在音乐信息检索（MIR）中仍未得到充分探索，尤其是在音乐源分离（MSS）任务方面。现有的立体声MSS模型虽能处理双耳音频，但常降低分离音轨的空间质量并削弱听众沉浸感。通过一项比较双耳和立体声MSS输出的感知研究，评估客观空间失真指标与人类感知的关联程度。结果显示这些指标与人类判断的一致性各异，用于评估双耳音乐任务时缺乏可靠性。具体而言，双耳时间差（ITD）估计对噪声和分离伪像高度敏感。在评估两种替代ITD估计方法时，发现稳健性和准确性之间存在关键权衡，尤其是对于像贝斯这样的窄带乐器。这些结果强调需要为双耳音乐设计准确、可解释的空间指标，以开发能保留声源定位和听众沉浸感的模型。
英文摘要
Despite the rising popularity of immersive audio, binaural music remains underexplored in music information retrieval (MIR), particularly regarding the task of music source separation (MSS). While existing stereo MSS models can process binaural audio, they often degrade the spatial quality of the separated stems and undermine listener immersion. Through a perceptual study comparing binaural and stereo MSS outputs, we evaluate how well objective spatial distortion metrics correlate with human perception. Our findings reveal varied agreement between these metrics and human judgment, highlighting a lack of reliability when used to evaluate binaural music tasks. Specifically, we find that Interaural Time Difference (ITD) estimation is highly sensitive to noise and separation artifacts. In evaluating two alternative ITD estimation methods, we uncover a critical trade-off between robustness and accuracy, particularly for narrow-band instruments like bass. These results underscore the need for accurate, interpretable spatial metrics designed for binaural music to develop models that preserve source localization and listener immersion.
Comments6 pages + references, 6 figures, 1 table, 27th International Society for Music Information Retrieval (ISMIR) Conference
