Datasets:
ArXiv:
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Update dataset card links and wording
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README.md
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@@ -4,8 +4,15 @@ license: mit
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# b150_official_train
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This release contains the high-confidence `b150` training split used by MAGIC-TTS
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Stats:
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- Total samples: `201986`
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- `selected_samples.exported.jsonl`: manifest with `sample_id`, `utt_id`, `language`, `audio_path`, `duration`, and `target_text`
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- `raw_audio_en.tar.part-*`: split English raw audio bundle
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- `raw_audio_zh.tar.part-*`: split Chinese raw audio bundle
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- `mfa_sidecars.tar.part-*`: split standalone MFA word-level alignments with relative `audio_path`
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Notes:
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- Reconstruct tar files first:
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# b150_official_train
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This release contains the high-confidence `b150` training split used by MAGIC-TTS,
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with standalone MFA word-level alignments distributed separately from prepared Arrow
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artifacts.
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Related links:
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- GitHub repo: https://github.com/yongaifadian1/MAGIC-TTS
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- arXiv paper: https://arxiv.org/abs/2604.21164
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- Open-source model: https://huggingface.co/maimai11/MAGIC-TTS
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- Online demo: https://yongaifadian1.github.io/MAGIC-TTS/
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Stats:
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- Total samples: `201986`
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- `selected_samples.exported.jsonl`: manifest with `sample_id`, `utt_id`, `language`, `audio_path`, `duration`, and `target_text`
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- `raw_audio_en.tar.part-*`: split English raw audio bundle
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- `raw_audio_zh.tar.part-*`: split Chinese raw audio bundle
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- `mfa_sidecars.tar.part-*`: split standalone MFA word-level alignments with relative `audio_path`, ready to be reused during local dataset preparation
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Notes:
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- Reconstruct tar files first:
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