论文标题
重新映射，扭曲和参加：非平行的多对面重音转换，正常流量
Remap, warp and attend: Non-parallel many-to-many accent conversion with Normalizing Flows
论文作者
论文摘要
同一语言的区域口音不仅会影响单词的发音方式（即语音内容），还会影响语音的韵律方面，例如说话率和语调。本文使用归一化流量研究了一种基于流动的新方法来进行重音转化。提出的方法围绕三个步骤旋转：重新映射语音条件，以更好地匹配目标口音，扭曲转换后的语音持续时间，以更好地适合目标音素，以及一种隐含地对准源和目标语音序列的注意机制。所提出的重新映射系统可以适应语音的语音和韵律方面，同时允许源和转换的语音信号具有不同的长度。客观和主观评估表明，所提出的方法在与目标口音，自然性和清晰度方面相似，大大优于竞争性模仿基线模型。
Regional accents of the same language affect not only how words are pronounced (i.e., phonetic content), but also impact prosodic aspects of speech such as speaking rate and intonation. This paper investigates a novel flow-based approach to accent conversion using normalizing flows. The proposed approach revolves around three steps: remapping the phonetic conditioning, to better match the target accent, warping the duration of the converted speech, to better suit the target phonemes, and an attention mechanism that implicitly aligns source and target speech sequences. The proposed remap-warp-attend system enables adaptation of both phonetic and prosodic aspects of speech while allowing for source and converted speech signals to be of different lengths. Objective and subjective evaluations show that the proposed approach significantly outperforms a competitive CopyCat baseline model in terms of similarity to the target accent, naturalness and intelligibility.
