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arXiv · 2408.12170

VoiceX: A Text-To-Speech Framework for Custom Voices

Silvan Mertes·Daksitha Withanage Don·Otto Grothe·Johanna Kuch·Ruben Schlagowski·Elisabeth André
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Abstract

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.

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Silvan Mertes, Daksitha Withanage Don, Otto Grothe, Johanna Kuch, Ruben Schlagowski, Elisabeth André. 2024-08-22. VoiceX: A Text-To-Speech Framework for Custom Voices. https://arxiv.org/abs/2408.12170

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