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Add Russian CosyVoice 3 dubbing pack and audio gallery
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Russian CosyVoice 3 dubbing pack

This directory adds a reproducible Russian voice-conversion route and 20 curated Russian GLaDOS samples. It does not add a native Russian checkpoint to the original GPT-SoVITS or Style-Bert-VITS2 models.

Pipeline

  1. The English Portal clip supplies the GLaDOS voice, timbre, formants, and delivery.
  2. RuAccent and Silero v4 generate a clean Russian content track.
  3. Rubber Band matches the reference duration before VC, or after VC for lines listed in pipeline_controls.json.
  4. CosyVoice 3 inference_vc transfers the English reference voice onto the Russian content.
  5. A verified, formant-preserving Rubber Band pass aligns median F0 to the English reference.

manifest.jsonl maps every English reference, Russian translation, output sample, prosody profile, per-line control, and QA result. The references come from ray0rf1re/GLaDOS-audio-v2.

Reproduce

Clone FunAudioLLM/CosyVoice with its submodules and install its dependencies. Install the packages in requirements.txt and the rubberband command-line tool. Download FunAudioLLM/Fun-CosyVoice3-0.5B-2512, then run:

python download_refs.py
python generate_silero_sources.py --ruaccent-workdir .cache/ruaccent
python generate_cosyvoice_vc_batch.py \
  --cosyvoice-root /path/to/CosyVoice \
  --model-dir /path/to/Fun-CosyVoice3-0.5B-2512

Use --overwrite to rebuild existing intermediates. The default directories are relative to this folder, and --ids 0234 0258 can limit a run.

Validation

All 20 published WAV files pass these checks:

  • 24 kHz, mono, PCM16;
  • absolute duration difference from the English reference at most 0.08 seconds;
  • peak amplitude at most 0.951;
  • median-F0 relative error at most 2.5%;
  • GigaAM multilingual CTC word error rate at most 10% per clip.

The checked run produced 17 word-exact clips, 1.36% mean WER, and 9.09% maximum WER. Re-run it with:

python qa_cosyvoice_batch.py --asr --outputs samples

See qa_report.json for per-clip measurements and transcripts. The sample pack was generated with Silero, RuAccent, CosyVoice 3, and Rubber Band. The original repository license and the source/model terms continue to apply.