论文标题
关于声学音乐信号的音调估算的几何框架
A Geometric Framework for Pitch Estimation on Acoustic Musical Signals
论文作者
论文摘要
本文提出了一种几何方法来进行音调估计（PE） - 音乐信息检索中的重要问题（MIR），以及该领域其他各种问题的先驱。尽管存在许多高度精确的方法，但单点估计和多诉估计（尤其是未指定的多音音色）在计算和概念上都具有挑战性。许多当前的技术虽然非常有效，但并非旨在引起基础的基础数学结构，这些数学结构是声学音乐信号所表现出的复杂音乐模式。从理论和实验性的角度来解决方法时，我们提出了一个新颖的框架，是该领域进一步工作的基础，结果（尽管不是最新的）表现出相对效率。本文介绍的框架为解决PE问题提供了一种全新的方法，并可能在传统的分析方法以及当前主导文献主导的新兴机器学习（ML）方法中使用了。
This paper presents a geometric approach to pitch estimation (PE)-an important problem in Music Information Retrieval (MIR), and a precursor to a variety of other problems in the field. Though there exist a number of highly-accurate methods, both mono-pitch estimation and multi-pitch estimation (particularly with unspecified polyphonic timbre) prove computationally and conceptually challenging. A number of current techniques, whilst incredibly effective, are not targeted towards eliciting the underlying mathematical structures that underpin the complex musical patterns exhibited by acoustic musical signals. Tackling the approach from both a theoretical and experimental perspective, we present a novel framework, a basis for further work in the area, and results that (whilst not state of the art) demonstrate relative efficacy. The framework presented in this paper opens up a completely new way to tackle PE problems, and may have uses both in traditional analytical approaches, as well as in the emerging machine learning (ML) methods that currently dominate the literature.
