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slotvox

End-to-end spoken language understanding toolkit: a small trainable neural audio codec with RVQ, joint intent-and-slot models over speech features, streaming partial intents, a speech-LLM instruction data pipeline, and turn-level evaluation with reproducible reports. NumPy core with a CPU-only torch extra; synthetic data only, fully offline.

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GITHUB · launched Sep 26, 2026 · 36 upvotes (top 23%) · 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
  • end-to-end
  • instruction-data
  • intent-detection
  • neural-audio-codec
  • numpy
  • python
  • +5 more

Visit website ↗ Source listing ↗

Could you build this?

No Training custom neural audio codecs with residual vector quantization (RVQ) and joint intent/slot models from scratch requires specialized machine learning and speech processing research expertise.

What it would actually take: Architecture consists of custom PyTorch/NumPy acoustic encoders, vector-quantized latent representations (RVQ), streaming recurrent/transformer SLU heads, and synthetic speech synthesis pipelines. The hardest parts are acoustic codec training stability, low-latency streaming discretization on CPU without quantization noise, and domain-specific audio ML engineering.

Competitors

Other products that read as similar to this one : 1318 launches clear the similarity bar, closest 8 shown.

Attention rank: #336 of 1319 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 331 days after the earliest competitor.

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.