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Fix test wav files in FunASR Nano models. - #3004

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csukuangfj merged 1 commit into
k2-fsa:masterfrom
csukuangfj:upload-models
Jan 7, 2026
Merged

csukuangfj merged 1 commit into
k2-fsa:masterfrom
csukuangfj:upload-models

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@csukuangfj csukuangfj commented Jan 7, 2026 •

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Summary by CodeRabbit

Release Notes

  • Chores
    • Updated CI workflow to standardize audio file formatting to 16-bit mono WAV.
    • Enhanced build process to handle multiple model variants in packaging.
    • Added ffmpeg installation for audio processing in CI environment.

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@dosubot dosubot Bot added the size:M This PR changes 30-99 lines, ignoring generated files. label Jan 7, 2026
@csukuangfj
csukuangfj merged commit 5f12b08 into k2-fsa:master Jan 7, 2026
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coderabbitai Bot commented Jan 7, 2026 •

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📝 Walkthrough

Walkthrough

Modifies the CI workflow to install ffmpeg, replace single sherpa-onnx-funasr-nano model handling with a multi-model loop across three variants, and add WAV audio normalization steps to convert files to 16-bit mono. Disables the Hugging Face publishing condition.

Changes

Cohort / File(s) Summary
CI Workflow Enhancement
.github/workflows/upload-models.yaml
Adds ffmpeg installation and verification; replaces single-model collection block with multi-model loop iterating three sherpa-onnx-funasr-nano variants (int8, float32, float16); inserts WAV normalization steps (ffmpeg 16-bit mono conversion) after downloading test_wavs in model collection sections; disables Hugging Face publishing step (condition changed from true to false).

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~8 minutes

Poem

🐰 With ffmpeg's magic touch so fine,
We normalize each WAV to align,
Three models now, not one, parade,
Through workflow loops our builds are made,
Audio's cleaner, code's pristine! ✨


📜 Recent review details

Configuration used: defaults

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 8d28e72 and 868abcb.

📒 Files selected for processing (1)
  • .github/workflows/upload-models.yaml

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