音乐信息检索（MIR）的目标是开发技术和工具，以一种健壮、高效和智能的方式组织、理解和搜索大型音乐收藏中的多模态信息。在这种背景下，本文提出了新颖的、基于内容的音乐同步、音频匹配和源分离方法。一般来说，音乐同步指的是，对于一段音乐的一种表现形式中的给定位置，确定另一种表现形式中的相应位置的过程。在这里，本文提出了三种互补的同步方法，它们在鲁棒性、可靠性和精确性方面都有改进。第一种方法采用一种基于多个概念上不同的对齐技术的后期融合策略来识别那些允许可靠对齐结果的音乐段落。第二种方法基于在同步背景下使用音乐结构分析方法来获得可靠的同步结果，即使在需要对齐的版本之间存在结构差异的情况下也是如此。最后，第三种方法采用了几种互补策略来提高同步结果的精度和时间分辨率。

给定一个简短的待查询音频片段，音频匹配的目标是自动检索相同音乐的不同版本和安排中所有音乐相似的摘录。在这种情况下，基于色度的音频特征是一个公认的工具，因为它们对音色的变化具有高度的不变性。本文描述了一种新的方法，使色度特征对音色变化更为稳健，同时保持其鉴别能力。在这里，我们的想法是使用受众所周知的MFCC特征启发技术来识别和丢弃与音色相关的信息，这些特征通常用于语音处理。

对于单声道音乐录制，源分离的目标是从录音中提取出与旋律、乐器或鼓点相对应的有音乐意义的声源。为了方便这项复杂的任务，人们可以利用乐谱提供的附加信息。基于这一思想，本文提出了两种新颖的、概念上不同的信源分离方法。第一种方法利用给定MIDI文件提供的乐谱信息，使用参数化模型来描述给定的音乐录音，然后使用得到的模型来提取由评分指定的声源。第二种方法利用额外的评分信息来指导基于非负定矩阵分解（NMF）的分解，计算量小，易于实现。

The field of music information retrieval (MIR) aims at developing techniques and tools for organizing, understanding, and searching multimodal information in large music collections in a robust, efficient and intelligent manner. In this context, this thesis presents novel, content-based methods for music synchronization, audio matching, and source separation. In general, music synchronization denotes a procedure which, for a given position in one representation of a piece of music, determines the corresponding position within another representation. Here, the thesis presents three complementary synchronization approaches, which improve upon previous methods in terms of robustness, reliability, and accuracy. The first approach employs a late-fusion strategy based on multiple, conceptually different alignment techniques to identify those music passages that allow for reliable alignment results. The second approach is based on the idea of employing musical structure analysis methods in the context of synchronization to derive reliable synchronization results even in the presence of structural differences between the versions to be aligned. Finally, the third approach employs several complementary strategies for increasing the accuracy and time resolution of synchronization results. Given a short query audio clip, the goal of audio matching is to automatically retrieve all musically similar excerpts in different versions and arrangements of the same underlying piece of music. In this context, chroma-based audio features are a well-established tool as they possess a high degree of invariance to variations in timbre. This thesis describes a novel procedure for making chroma features even more robust to changes in timbre while keeping their discriminative power. Here, the idea is to identify and discard timbre-related information using techniques inspired by the well-known MFCC features, which are usually employed in speech processing. Given a monaural music recording, the goal of source separation is to extract musically meaningful sound sources corresponding, for example, to a melody, an instrument, or a drum track from the recording. To facilitate this complex task, one can exploit additional information provided by a musical score. Based on this idea, this thesis presents two novel, conceptually different approaches to source separation. Using score information provided by a given MIDI file, the first approach employs a parametric model to describe a given audio recording of a piece of music. The resulting model is then used to extract sound sources as specified by the score. As a computationally less demanding and easier to implement alternative, the second approach employs the additional score information to guide a decomposition based on non-negative matrix factorization (NMF).

1.  引言

2.  色度特征

3.  音色不变音频特征

4.  对齐方法

5.  基于延迟融合的部分同步

6.  面向结构的部分同步

7.  高精度音乐同步

8.  评分驱动的信源分离

9.  音频参数化

10.          评分驱动的非负定矩阵分解

11.          结论与展望

附录A 色度工具箱

附录B CRP评估的技术细节

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