为音乐和声生成设计聚合算法，提升集体建议的表达力与音乐连贯性。
Algorithms for Collaborative Harmonization
- 基于群体建议构建和声序列的聚合算法
- Kemeny与多数投票算法在表达与连贯性上表现最佳
- 适合音乐生成与人机协作创作研究者
我们研究音乐和声中的特定文本聚合场景。和声与一般文本聚合类似，但其语言结构更严谨。给定一组针对特定旋律的和声建议，目标是设计聚合算法，生成同时满足两个关键条件的和声序列：(1) 有效体现集体建议；(2) 具有音乐连贯性。本文提出多种代理群体和声聚合算法，并分析其复杂度。结果表明，Kemeny 和多数投票算法在代表性和音乐连贯性方面表现最优。
原文摘要 · Abstract (English)
We consider a specific scenario of text aggregation, in the realm of musical harmonization. Musical harmonization shares similarities with text aggregation, however the language of harmony is more structured than general text. Concretely, given a set of harmonization suggestions for a given musical melody, our interest lies in devising aggregation algorithms that yield an harmonization sequence that satisfies the following two key criteria: (1) an effective representation of the collective suggestions; and (2) an harmonization that is musically coherent. We present different algorithms for the aggregation of harmonies given by a group of agents and analyze their complexities. The results indicate that the Kemeny and plurality-based algorithms are most effective in assessing representation and maintaining musical coherence.
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