RI: SMALL: Modeling Voice Source Transformation in Monolingual and Crosslingual Non-parallel Voice Conversion Applications

语音转换（VC）系统转换来自给定源说话人的语音片段，以便可以识别为由指定的目标说话人所说。目前，标准的VC系统需要在广泛标记的语音数据集上进行并行训练，其中源和目标说话人共享用于构建直接映射模型的等效内容。该项目建立在nonparallelVC系统的概念上，减少了源和目标扬声器之间对标记和共享语音内容的需求，并允许语言内和跨语言转换场景。该项目主要集中在两个方面：（1）建立一个非并行VC框架，没有明确的语音，声音，单词或句子级别的标签，（2）提供有效的目标说话人映射，以获得与当前VC系统一样好或更好的转换语音。VC框架由三个主要部分组成：（1）说话人无关语言模型，（2）模型自适应算法，（3）模型自适应算法。（3）语音合成模块，用于从目标语言模型生成转换语音。该项目将为辅助文本语音转换（TTS）系统的个性化，外语学习，并且作为语音到语音翻译系统中的可能组件。这个项目将支持研究生的研究，并通过会议和期刊提交为社区分发提供结果。此外，还将开发和免费分发一套开放源码软件工具。该项目还将用于科学、技术、工程和数学学科中代表性不足的群体的外联活动。

Voice conversion (VC) systems transform segments of speech from a given source speaker so that itcan be identified as spoken by a specified target speaker. Currently, standard VC systems requireparallel training on extensively labeled sets of speech data where the source and target speaker shareequivalent content for building direct mapping models. This project builds on the concepts of nonparallelVC systems reducing the need for labeled and shared speech content between source and targetspeakers as well as allowing for both intra-lingual and cross-lingual conversion scenarios. This projectfocuses on two main areas: (1) Building a framework for non-parallel VC without explicit phonetic,sound, word, or sentence level labels, and (2) Providing effective target speaker mapping to obtainconverted speech with as good as or better quality compared to current VC systems. The VCframework consists of three main components: (1) A speaker independent language model; (2) Analgorithm for model adaptation to target speaker; (3) A speech synthesis block to generate convertedspeech from a target-adapted language model.This project will provide a broad framework for applications such as personalization of assistive textto-speech (TTS) systems, foreign language learning, and as a possible component in speech-to-speechtranslation systems. This project will support graduate student research and provide results forcommunity distribution through conference and journal submission. Additionally, an open-sourcesoftware toolset will be developed and freely distributed. The project will also be used in outreach forunderrepresented groups in Science Technology Engineering and Mathematics (STEM) disciplines.