论文标题
一个基于深度学习的分析合成框架，用于统一唱歌
A Deep Learning Based Analysis-Synthesis Framework For Unison Singing
论文作者
论文摘要
Unison Singing是同时演唱相同旋律和歌词的歌手合奏的名字。虽然每个单独的歌手都以相同的原则旋律唱歌，但歌手之间存在一些时机和音调偏差，而歌手与时间表的合奏一起，使听众具有“统一”感。在本文中，我们介绍了合唱团背景下的统一唱歌的研究。利用一些最近提出的基于深度学习的方法，我们分析了单个歌手在统一混合物的录音中的基本频率（F0）分布。基于分析，我们提出了一个系统，用于从无伴奏合唱的输入和代表统一混合物的单个语音原型合成一个单一信号。我们使用主观听力测试来评估我们提出的合成系统的感知因素，包括质量，遵守旋律以及感知的一致性程度。
Unison singing is the name given to an ensemble of singers simultaneously singing the same melody and lyrics. While each individual singer in a unison sings the same principle melody, there are slight timing and pitch deviations between the singers, which, along with the ensemble of timbres, give the listener a perceived sense of "unison". In this paper, we present a study of unison singing in the context of choirs; utilising some recently proposed deep-learning based methodologies, we analyse the fundamental frequency (F0) distribution of the individual singers in recordings of unison mixtures. Based on the analysis, we propose a system for synthesising a unison signal from an a cappella input and a single voice prototype representative of a unison mixture. We use subjective listening tests to evaluate perceptual factors of our proposed system for synthesis, including quality, adherence to the melody as well the degree of perceived unison.
