VoiceX：一个用于自定义声音的文本转语音框架
VoiceX: A Text-To-Speech Framework for Custom Voices
AI总结：
针对深度学习TTS模型参数空间庞大且不可解释导致手动自定义声音困难的问题，提出基于进化算法的人在回路范式与图形界面VoiceX，支持高效创建个性化自定义声音并提供Python API。
摘要：
现代TTS系统能够创建高度逼真且听起来自然的语音。尽管有这些进展，自定义TTS声音的过程仍然是一项复杂的任务，通常需要该领域专家的专业知识。其中一个原因是深度学习模型的使用，其特征是庞大的、不可解释的参数空间，限制了手动自定义的可行性。在本文中，我们提出了一种基于进化算法的新型人在回路范式，用于直接与神经TTS模型的参数空间进行交互。我们将该方法集成到一个用户友好的图形用户界面中，允许用户高效地创建原创声音。这些声音随后可以与骨干TTS模型一起使用，我们为此提供了一个Python API。此外，我们还展示了一项探索VoiceX能力的用户研究结果。我们证明VoiceX是创建个性化自定义声音的合适工具。
英文摘要：
Modern TTS systems are capable of creating highly realistic and natural-sounding speech. Despite these developments, the process of customizing TTS voices remains a complex task, mostly requiring the expertise of specialists within the field. One reason for this is the utilization of deep learning models, which are characterized by their expansive, non-interpretable parameter spaces, restricting the feasibility of manual customization. In this paper, we present a novel human-in-the-loop paradigm based on an evolutionary algorithm for directly interacting with the parameter space of a neural TTS model. We integrated our approach into a user-friendly graphical user interface that allows users to efficiently create original voices. Those voices can then be used with the backbone TTS model, for which we provide a Python API. Further, we present the results of a user study exploring the capabilities of VoiceX. We show that VoiceX is an appropriate tool for creating individual, custom voices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
