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A high-performance UTAU resampler based on pc-nsf-hifigan, rewritten in Go.

go hifigan hifisampler onnx openutau
12
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100% credibility
Found Apr 02, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

A high-performance drop-in replacement resampler for UTAU vocal synthesis software using neural vocoding for faster rendering of singing voices.

How It Works

1
🔍 Discover faster singing voices

You hear about hifisampler-go, a tool that makes creating songs with virtual singers in UTAU much quicker and smoother.

2
📥 Grab the ready files

Download the simple files made just for your computer from the releases page.

3
🚀 Start the magic helper

Click to launch the helper – it automatically gets the voice brains it needs and waits quietly in the background.

4
🎵 Link it to your song maker

Point your UTAU program to use this new helper, so it calls on it whenever rendering voices.

5
⚡ Render your song

Hit play in UTAU – watch notes turn into beautiful singing super fast, even with fancy effects like breath or growl.

🎉 Hear your creation shine

Your vocal track is done quickly with pro-sounding quality, ready to mix into your full song.

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AI-Generated Review

What is hifisampler-go?

hifisampler-go is a high-performance UTAU resampler rewritten in Go from the original Python version, based on the pc-nsf-hifigan neural vocoder. It processes voice samples into rendered audio for UTAU/OpenUTAU, delivering 2.75x faster GPU rendering and single-binary deployment with lower memory use. Run a server for HTTP/TCP/IPC clients that handle dozens of notes per second via drop-in executables.

Why is it gaining traction?

It crushes the original's slow startup and high RAM footprint, with auto-detecting GPU backends like TensorRT (10-30x vocoder speedup), CUDA, CoreML, and even Qualcomm NPU. IPC mode eliminates network overhead for real-time OpenUTAU workflows, while feature caching and ONNX models ensure compatibility with existing UTAU voicebanks. Go's speed makes it a high-performance backend alternative to C++ tools on GitHub.

Who should use this?

UTAU/OpenUTAU producers rendering long tracks who hit CPU/GPU bottlenecks. Voice modders tweaking breath, tension, or growl effects via flags like Hb/Hv/HG. Synth devs building high-performance browser or desktop apps needing fast resampling without Python deps.

Verdict

Solid rewrite for UTAU speed demons—grab the prebuilt binaries and test TensorRT if you've got NVIDIA. With just 12 stars and 1.0% credibility, it's early-stage (light tests, basic docs), so monitor for stability before production.

(187 words)

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