Developing multilingual speech synthesis system for Ojibwe, Mi'kmaq, and Maliseet
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Abstract (arXiv)
We present lightweight flow matching multilingual text-to-speech (TTS) systems for Ojibwe, Mi'kmaq, and Maliseet, three Indigenous languages in North America. Our results show that training a multilingual TTS model on three typologically similar languages can improve the performance over monolingual models, especially when data are scarce. Attention-free architectures are highly competitive with self-attention architecture with higher memory efficiency. Our research not only advances technical development for the revitalization of low-resource languages but also highlights the cultural gap in human evaluation protocols, calling for a more community-centered approach to human evaluation.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 14 of its 33 references that are in the map. First posted on arXiv 4 Feb 2025.
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References · 14
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- 2020HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesiscited by 1,154
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- 2023Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesiscited by 153
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- 2024Hydra: Bidirectional State Space Models Through Generalized Matrix Mixerscited by 44
- 2024Exploring the Capability of Mamba in Speech Applicationscited by 20
- 2024CM-TTS: Enhancing Real Time Text-to-Speech Synthesis Efficiency through Weighted Samplers and Consistency Modelscited by 13
2 more
- 2024FreeV: Free Lunch For Vocoders Through Pseudo Inversed Mel Filtercited by 6
- 2024MunTTS: A Text-to-Speech System for Mundaricited by 1
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Citing papers per year: 2025: 1.
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- 2025Align2Speak: Improving TTS for Low Resource Languages via ASR-Guided Online Preference Optimization
- 2026PFluxTTS: Hybrid Flow-Matching TTS with Robust Cross-Lingual Voice Cloning and Inference-Time Model Fusion
- 2026Bolbosh: Script-Aware Flow Matching for Kashmiri Text-to-Speech
- 2026Breaking the Curse of Multilinguality in Many-to-Many Speech-to-Text Translation via a Resource-Aware Mixture of Speech Encoders
- 2025LatinX: Aligning a Multilingual TTS Model with Direct Preference Optimization
- 2025DiaMoE-TTS: A Unified IPA-Based Dialect TTS Framework with Mixture-of-Experts and Parameter-Efficient Zero-Shot Adaptation
- 2025ManchuTTS: Towards High-Quality Manchu Speech Synthesis via Flow Matching and Hierarchical Text Representation
- 2023Cross-lingual Knowledge Distillation via Flow-based Voice Conversion for Robust Polyglot Text-To-Speech