标题： 降解不变的音乐索引 显示英文标题

标题： Degradation-Invariant Music Indexing

摘要： 为了构建对声音退化具有鲁棒性且适用于大规模音乐目录的音乐索引方法，本研究报告了一种基于与音乐内容相关的音频描述符的方法，并且这些描述符对声音变换（如噪声添加、失真、有损编码、音高/时间变换或滤波等）具有不变性。 为了实现这一目标，所提出方法的关键点之一是对高维音频特征的定义，这些特征本质上（通过设计）对某些声音退化具有鲁棒性。 然后利用这种表示的高维度来学习一个线性投影到显著较小的子空间，这通过一系列判别分析再次降低了对声音退化的敏感性。 最后，通过对选定的起始函数局部最大值进行时间锚定，执行一种近似哈希处理，以提供更好的比特损坏容错能力，同时使该方法更容易扩展。 显示英文摘要

摘要： For music indexing robust to sound degradations and scalable for big music catalogs, this scientific report presents an approach based on audio descriptors relevant to the music content and invariant to sound transformations (noise addition, distortion, lossy coding, pitch/time transformations, or filtering e.g.). To achieve this task, one of the key point of the proposed method is the definition of high-dimensional audio prints, which are intrinsically (by design) robust to some sound degradations. The high dimensionality of this first representation is then used to learn a linear projection to a sub-space significantly smaller, which reduces again the sensibility to sound degradations using a series of discriminant analyses. Finally, anchoring the analysis times on local maxima of a selected onset function, an approximative hashing is done to provide a better tolerance to bit corruptions, and in the same time to make easier the scaling of the method.