feat[cv2-2]: Data preparation (LibriTTS dev-clean subset -> parquet)
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Description
Goal
Iteration 2 of SPADE-on-CosyVoice2: download a small LibriTTS part, select a deterministic subset, extract speaker embeddings (campplus.onnx) and 25Hz speech tokens (speech_tokenizer_v2.onnx) with CPU onnxruntime, and write CosyVoice2-format parquet shards with train/eval splits.
Acceptance
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spade_cosyvoice2/data_prep.pydownloads LibriTTS (openslr), builds wav/text/spk tables, extracts embeddings + speech tokens, writes parquet + train/eval data.list files - CosyVoice's dataset pipeline can read the parquet and yield padded batches with text_token/speech_token/embedding
- Unit test for utterance collection; existing pytest suite passes
Notes
Iteration 2 for: SPADE applied to CosyVoice 2 (arXiv:2509.20802)
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
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- Fork the repository and make your change on a branch.
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Research direction
Start with spade_cosyvoice2/data_prep.py and inspect the existing CosyVoice dataset pipeline before implementing the LibriTTS subset flow. Add the named utterance-collection unit test and run the existing pytest suite. Done means parquet shards and train/eval data.list files are produced, and the pipeline yields padded batches containing text_token, speech_token, and embedding.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- audio-video-rtc, data-engineering, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100