Creating New Language and Voice Components for the Updated MaryTTS Text-to-Speech Synthesis Platform
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Dec 2017.
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Citing papers per year: 2024: 2; 2025: 0; 2026: 1.
3 papers.
- 2024ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scalecited by 88
- 2024Augmentation through Laundering Attacks for Audio Spoof Detectioncited by 0
- 2026What You Train Is What You Get: Gender Bias, Training Composition, and Post-Hoc Mitigation in Audio Deepfake Detectioncited by 0
- 2026What You Train Is What You Get: Gender Bias, Training Composition, and Post-Hoc Mitigation in Audio Deepfake Detection10 Jul 2026
- 2024Augmentation through Laundering Attacks for Audio Spoof Detection1 Oct 2024
- 2024ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale16 Aug 2024