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

语音转换（VC）系统对给定源说话人的语音片段进行转换，使其可以被识别为由指定的目标说话人说的。目前，标准的VC系统需要对广泛标记的语音数据集进行并行训练，其中源和目标说话者共享相同的内容，以构建直接映射模型。该项目建立在非并行vc系统的概念之上，减少了源和目标说话者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。该项目侧重于两个主要领域：(1)为非并行VC构建一个框架，没有明确的语音，声音，单词或句子级别标签；(2)提供有效的目标说话者映射，以获得与当前VC系统一样好或更好质量的转换语音。vc框架由三个主要部分组成：(1)独立于说话者的语言模型；(2)针对目标说话人的模型自适应算法；(3)从目标适应语言模型生成转换语音的语音合成块。该项目将为辅助文本到语音（TTS）系统的个性化、外语学习等应用提供一个广泛的框架，并可能成为语音到语音翻译系统的一个组成部分。该项目将支持研究生的研究，并通过会议和期刊提交为社区提供成果。此外，一个开源软件工具集将被开发并自由分发。该项目还将用于科学、技术、工程和数学（STEM）学科中代表性不足的群体的外展。

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.