标题： 未见过的说话人和语言适应用于带有适配器的轻量级文本到语音 显示英文标题

标题： Unseen Speaker and Language Adaptation for Lightweight Text-To-Speech with Adapters

摘要： 在本文中，我们通过适配器的视角研究跨语言文本到语音（TTS）合成，在轻量级TTS系统背景下。 特别是，我们将未见说话人和语言适应的任务进行比较，目标是在目标语言中合成目标语音，其中目标语音没有在该语言中的录音。 客观评估的结果表明，适配器在学习语言特定和说话人特定信息方面的有效性，使预训练模型能够学习未见过的说话人身份或语言，同时避免原始模型的说话人或语言信息的灾难性遗忘。 此外，为了衡量生成语音在口音方面的自然程度，我们提出并验证了一个受第二语言（L2）学习者发音错误检测技术启发的客观度量标准。 本文还提供了关于适配器放置、配置以及使用的说话人数目的影响的见解。 显示英文摘要

摘要： In this paper we investigate cross-lingual Text-To-Speech (TTS) synthesis through the lens of adapters, in the context of lightweight TTS systems. In particular, we compare the tasks of unseen speaker and language adaptation with the goal of synthesising a target voice in a target language, in which the target voice has no recordings therein. Results from objective evaluations demonstrate the effectiveness of adapters in learning language-specific and speaker-specific information, allowing pre-trained models to learn unseen speaker identities or languages, while avoiding catastrophic forgetting of the original model's speaker or language information. Additionally, to measure how native the generated voices are in terms of accent, we propose and validate an objective metric inspired by mispronunciation detection techniques in second-language (L2) learners. The paper also provides insights into the impact of adapter placement, configuration and the number of speakers used.