论文标题
与三合会的自动旋律协调：比较研究
Automatic Melody Harmonization with Triad Chords: A Comparative Study
论文作者
论文摘要
几项先前的作品提出了各种自动旋律协调任务的方法，其中模型旨在生成一系列和弦，以作为给定多杆旋律序列的谐波伴奏。在本文中，我们提出了一项比较研究，以评估和比较一组规范方法对此任务的性能，包括基于模板匹配的模型，一个基于隐藏的马尔可夫模型，基于遗传算法的模型和两个基于深度学习的模型。该评估是在我们新收集的9,226个旋律/和弦对的数据集上进行的，该研究使用标准化的训练/测试拆分，考虑了多达48个三合会的和弦。我们报告了使用六个不同的指标和一项主观研究的客观评估的结果。
Several prior works have proposed various methods for the task of automatic melody harmonization, in which a model aims to generate a sequence of chords to serve as the harmonic accompaniment of a given multiple-bar melody sequence. In this paper, we present a comparative study evaluating and comparing the performance of a set of canonical approaches to this task, including a template matching based model, a hidden Markov based model, a genetic algorithm based model, and two deep learning based models. The evaluation is conducted on a dataset of 9,226 melody/chord pairs we newly collect for this study, considering up to 48 triad chords, using a standardized training/test split. We report the result of an objective evaluation using six different metrics and a subjective study with 202 participants.
