多种歌声中音高提取算法的比较研究（CS CompLang）

• 2020 年 1 月 2 日
• 笔记

语音研究界已经广泛研究了音调跟踪的问题。 本文的目的是研究如何将这些技术应用于歌唱语音分析，并对具代表性的最新方法进行比较评估。 这项研究是在带注释歌声的大型数据库上进行的，这些数据库带有对齐的EGG录音，包括各种歌手类别和唱歌练习。 算法性能是根据检测语音边界和准确估计音高轮廓的能力来评估的。 首先，我们评估将现有方法用于歌唱语音分析的有用性。 然后，根据歌手类别和喉咙机制，比较几种音高提取算法的准确性。 最后，我们分析了它们对混响的鲁棒性。

原文题目：A Comparative Study of Pitch Extraction Algorithms on a Large Variety of Singing Sounds

原文：The problem of pitch tracking has been extensively studied in the speech research community. The goal of this paper is to investigate how these techniques should be adapted to singing voice analysis, and to provide a comparative evaluation of the most representative state-of-the-art approaches. This study is carried out on a large database of annotated singing sounds with aligned EGG recordings, comprising a variety of singer categories and singing exercises. The algorithmic performance is assessed according to the ability to detect voicing boundaries and to accurately estimate pitch contour. First, we evaluate the usefulness of adapting existing methods to singing voice analysis. Then we compare the accuracy of several pitch-extraction algorithms, depending on singer category and laryngeal mechanism. Finally, we analyze their robustness to reverberation.

原文作者：Onur Babacan,Thomas Drugman,Nicolas d'Alessandro,Nathalie Henrich,Thierry Dutoit

原文地址：https://arxiv.org/abs/1912.12609

多种歌声中音高提取算法的比较研究（CS CompLang）.pdf