Efficient Index-Based Audio Matching
Efficient Index-Based Audio Matching
复制标题
基于索引的高效音频匹配
DOI：
10.1109/tasl.2007.911552
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Meinard Müller
中科院分区：
文献类型：
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作者：
F. Kurth;Meinard Müller
给定一个庞大的音乐录音数据库，经典音频识别的目标是通过一个短音频片段来识别一个特定的音频记录。尽管最近的识别算法显示出对噪声、MP3压缩伪像和均匀时间畸变的显著鲁棒性，但相似性的概念与同一性相当接近。在本文中，我们解决了一个更高层次的检索问题，我们称之为音频匹配：给定一个简短的查询音频片段，目标是自动检索数据库中与查询音乐对应的所有录音的所有摘录。在我们的匹配场景中，与经典音频识别相反，我们允许语义上的变化，因为它们通常出现在对一段音乐的不同解释中。为此，本文提出了一种高效且鲁棒的音频匹配程序，即使在存在显著变化（如非线性时间、动态和频谱偏差）的情况下也能工作，而现有的音频识别算法在这些情况下会失败。此外，各种变形和容错机制的结合使我们能够采用标准索引技术来获得高效的、基于索引的匹配过程，从而为语义搜索大规模真实世界的音乐收藏提供了重要的一步。
Given a large audio database of music recordings, the goal of classical audio identification is to identify a particular audio recording by means of a short audio fragment. Even though recent identification algorithms show a significant degree of robustness towards noise, MP3 compression artifacts, and uniform temporal distortions, the notion of similarity is rather close to the identity. In this paper, we address a higher level retrieval problem, which we refer to as audio matching: given a short query audio clip, the goal is to automatically retrieve all excerpts from all recordings within the database that musically correspond to the query. In our matching scenario, opposed to classical audio identification, we allow semantically motivated variations as they typically occur in different interpretations of a piece of music. To this end, this paper presents an efficient and robust audio matching procedure that works even in the presence of significant variations, such as nonlinear temporal, dynamical, and spectral deviations, where existing algorithms for audio identification would fail. Furthermore, the combination of various deformation- and fault-tolerance mechanisms allows us to employ standard indexing techniques to obtain an efficient, index-based matching procedure, thus providing an important step towards semantically searching large-scale real-world music collections.