# speech-mine

> Use this tool when you need to extract valuable insights from audio data by converting it into searchable, speaker-labeled transcripts. It solves problems related to audio analysis, speaker identification, and information retrieval, ideal for iterative pipelines. The tool takes audio files as input and outputs searchable transcripts, making it perfect for applications requiring repeated processing and version control, such as those integrated with git.

Canonical page: https://skillsregistry.net/skills/beckettfrey-speech-mine  
JSON: https://api.skillsregistry.net/v1/skills/beckettfrey-speech-mine

## Description

Turn audio into searchable, speaker-labeled transcripts. Built for iterative pipelines, not one-shot runs.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** devops-ci
- **Updated:** 2026-04-23

## Source

- **Source listing:** [GitHub](https://github.com/BeckettFrey/speech-mine)

## 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": "beckettfrey-speech-mine"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/beckettfrey-speech-mine` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/beckettfrey-speech-mine/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