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Creating New Language and Voice Components for the Updated MaryTTS Text-to-Speech Synthesis Platform

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arxiv 1712.04787 v2 pith:T7LI3X27 submitted 2017-12-13 cs.CL cs.HC

Ingmar Steiner , Sébastien Le Maguer This is my paper · ORCID
classification cs.CLcs.HC
keywords maryttssynthesiscomponentsopenplatformtext-to-speechupdatedworkflow
verification ladder T0 review T1 audit T2 compute T3 formal
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We present a new workflow to create components for the MaryTTS text-to-speech synthesis platform, which is popular with researchers and developers, extending it to support new languages and custom synthetic voices. This workflow replaces the previous toolkit with an efficient, flexible process that leverages modern build automation and cloud-hosted infrastructure. Moreover, it is compatible with the updated MaryTTS architecture, enabling new features and state-of-the-art paradigms such as synthesis based on deep neural networks (DNNs). Like MaryTTS itself, the new tools are free, open source software (FOSS), and promote the use of open data.

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  1. MoLEx: Mixture of LoRA Experts in Speech Self-Supervised Models for Audio Deepfake Detection

    cs.SD 2025-09 conditional novelty 5.0 of 10

    MoLEx combines LoRA adapters with a top-K expert router inside a frozen WavLM model, achieving 5.56% EER on ASVSpoof 5 without augmentation.

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