谁觉得这个声音有吸引力？一项使用自然数据的大规模实验
Who Finds This Voice Attractive? A Large-Scale Experiment Using In-the-Wild Data
AI总结：
本文构建了大规模语音好感度语料库CocoNut-Humoresque，通过885名听者评分1800个语音片段，分析性别、年龄偏差及基频和x-vector等声学特征与好感度的关系。
摘要：
本文介绍了CocoNut-Humoresque，一个开源的大规模语音好感度语料库，包含语音片段及其每个听者的好感度评分。评估语音好感度对于为语音系统（如对话系统或播报系统）设计更受欢迎的声音至关重要。在本研究中，我们让885名听者对1800个来自广泛说话人的语音片段进行好感度评分。在构建语料库时，我们还收集了多个说话人属性：性别、年龄和最喜欢的YouTube视频。因此，该语料库支持从说话人和听者两方面因素对语音好感度进行大规模统计分析。本文描述了构建方法，并进行了初步数据分析，以揭示语音好感度中的性别和年龄偏差。此外，还研究了语音好感度与两个声学特征——给定话语的基频和x-vector——之间的关系。
英文摘要：
This paper introduces CocoNut-Humoresque, an open-source large-scale speech likability corpus that includes speech segments and their per-listener likability scores. Evaluating voice likability is essential to designing preferable voices for speech systems, such as dialogue or announcement systems. In this study, we let 885 listeners rate 1800 speech segments of a wide range of speakers regarding their likability. When constructing the corpus, we also collected the multiple speaker attributes: genders, ages, and favorite YouTube videos. Therefore, the corpus enables the large-scale statistical analysis of voice likability regarding both speaker and listener factors. This paper describes the construction methodology and preliminary data analysis to reveal the gender and age biases in voice likability. In addition, the relationship between the likability and two acoustic features, the fundamental frequencies and the x-vectors of given utterances, is also investigated.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
