论文标题
生成多语言性别歧义的文本到语音声音
Generating Multilingual Gender-Ambiguous Text-to-Speech Voices
论文作者
论文摘要
任何语音用户界面的性别是其感知身份的关键要素。最近，人们对性别歧义而不是明确识别为女性或男性的界面越来越兴趣。这项工作解决了在多语言设置中生成新颖的性别歧义TTS声音的任务。这是通过使用建议的性别感知方法从潜在扬声器嵌入空间嵌入空间的有效采样来完成的。广泛的客观和主观评估清楚地表明，该方法能够有效地产生一系列新颖，多样化的声音，这些声音比所有研究的语言中的基线语音都一致且视为性别含糊。有趣的是，在听众的两个人口统计学因素中发现性别感知是强大的：母语和性别。据我们所知，这是第一种系统和验证的方法，可以可靠地产生各种性别含糊的声音。
The gender of any voice user interface is a key element of its perceived identity. Recently, there has been increasing interest in interfaces where the gender is ambiguous rather than clearly identifying as female or male. This work addresses the task of generating novel gender-ambiguous TTS voices in a multi-speaker, multilingual setting. This is accomplished by efficiently sampling from a latent speaker embedding space using a proposed gender-aware method. Extensive objective and subjective evaluations clearly indicate that this method is able to efficiently generate a range of novel, diverse voices that are consistent and perceived as more gender-ambiguous than a baseline voice across all the languages examined. Interestingly, the gender perception is found to be robust across two demographic factors of the listeners: native language and gender. To our knowledge, this is the first systematic and validated approach that can reliably generate a variety of gender-ambiguous voices.
