OpenBibleTTS supplies speech data and alignments for 37 underrepresented languages and shows that no single TTS system leads on all metrics, with Gemini-TTS highest in listener ratings but monolingual EveryVoice models strongest on intelligibility for several African languages.
Skerry-Ryan and Daisy Stanton and Yonghui Wu and Ron J
2 Pith papers cite this work. Polarity classification is still indexing.
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Mixing 636 hours of LLM-generated synthetic conversations with 67 hours of real data outperforms a model trained on 2700 hours of real Hungarian speech on the BEA-Dialogue benchmark.
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OpenBibleTTS: Large-Scale Speech Resources and TTS Models for Low-Resource Languages
OpenBibleTTS supplies speech data and alignments for 37 underrepresented languages and shows that no single TTS system leads on all metrics, with Gemini-TTS highest in listener ratings but monolingual EveryVoice models strongest on intelligibility for several African languages.
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Efficient ASR Training with Conversations that Never Happened
Mixing 636 hours of LLM-generated synthetic conversations with 67 hours of real data outperforms a model trained on 2700 hours of real Hungarian speech on the BEA-Dialogue benchmark.