# genpark-dual-track-vector-quantized-acoustic-codec-skill

> genpark-dual-track-vector-quantized-acoustic-codec-skill — alphaparkinc-genpark-dual-track-vector-quantized-acoustic-codec-skill. Use this tool when you need to efficiently compress and transmit audio data, particularly in low-bitrate applications such as speech coding. It solves problems related to audio compression, transmission, and storage by utilizing dual-track vector quantization and neural audio coding techniques. This skill takes in audio input and outputs compressed audio data, ideal for use cases like voice assistants, podcasts, or audio streaming services.

Canonical page: https://skillsregistry.net/skills/alphaparkinc-genpark-dual-track-vector-quantized-acoustic-codec-skill  
JSON: https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-dual-track-vector-quantized-acoustic-codec-skill

## Description

Dual-track vector quantized acoustic codec & low-bitrate neural audio (Fish-Speech)

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/alphaparkinc/genpark-dual-track-vector-quantized-acoustic-codec-skill)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "alphaparkinc-genpark-dual-track-vector-quantized-acoustic-codec-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-dual-track-vector-quantized-acoustic-codec-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-dual-track-vector-quantized-acoustic-codec-skill/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt