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X-AuT

code repo for X-AuT: Progressive Audio-Encoder Compression for Speech LLMs with Cross-Scale Distillation

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GITHUB · launched Sep 10, 2026 · 10 upvotes (top 74%) · 0 views

Niche: speech and voice ai models · 143 launches, 7 in the last 7 days ▼ -30% · Explore this niche →

Category and tags

  • Horizontal
  • Model & infra
  • Developer
  • AI-native
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

No This is frontier ML research involving progressive neural network pruning, cross-scale model distillation, and training speech encoders on over 280,000 hours of audio data.

What it would actually take: Reproducing this requires a large multi-GPU compute cluster (H100/A100s), a proprietary or massive 280k+ hour speech dataset, and deep ML research expertise. The pipeline involves training paired teacher/student models, developing custom layer-interaction behavioral probes, implementing cross-scale intermediate representation alignment, and tuning scheduled policy distillation runs.

Competitors

Other products that read as similar to this one : 1617 launches clear the similarity bar, closest 8 shown.

Attention rank: #1196 of 1618 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 315 days after the earliest competitor.

  • UltraCompress · hn · 2026-05-08 · 6 upvotes · similarity 0.70
  • zipcodec · github · 2026-09-11 · 8 upvotes · similarity 0.66
  • speechloom · github · 2026-09-09 · 31 upvotes · similarity 0.66
  • winace-compression-suite · github · 2026-11-10 · 102 upvotes · similarity 0.64
  • pl-flow · github · 2026-10-07 · 18 upvotes · similarity 0.63
  • caramel · github · 2026-11-10 · 28 upvotes · similarity 0.63
  • voxweave · github · 2026-09-09 · 32 upvotes · similarity 0.60
  • ito · github · 2026-10-02 · 11 upvotes · similarity 0.60

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.