noizai/skills

speech-to-text

Use this skill whenever the user wants to transcribe audio to text, convert speech to text, or get a transcript from an audio or video file.

First seen May 7, 2026

Installation

$ npx skills add noizai/skills --skill speech-to-text

Summary

  • Use this skill whenever the user wants to transcribe audio to text, convert speech to text, or get a transcript from an audio or video file.
  • Triggers include: any mention of 'transcribe', 'transcription', 'speech to text', 'STT', 'convert audio to text', 'what does this audio say', 'get transcript', 'subtitle generation', or requests to extract spoken words from a file.
  • Also use when the user wants speaker identification from audio, timestamps for captions, or multilingual transcription.

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from noizai/skills.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 524
Default branch main
Open issues 3
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents clawdbot

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,688 B
  • docs SUMMARY.md 514 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 162 installs

SKILL.md

speech-to-text

Transcribe any audio file to text. Supports multilingual auto-detection, timestamps, and speaker labels.

Triggers

  • transcribe / transcript / transcription
  • speech to text / STT / audio to text
  • what does this audio say / convert audio
  • 转录 / 语音转文字 / 识别音频

Quick Start

# Transcribe with auto language detection
python3 skills/speech-to-text/scripts/stt.py audio.mp3

# Specify language explicitly
python3 skills/speech-to-text/scripts/stt.py interview.wav --language en

# Save transcript to file
python3 skills/speech-to-text/scripts/stt.py podcast.m4a -o transcript.txt

# Output full JSON (with timestamps and speaker labels)
python3 skills/speech-to-text/scripts/stt.py meeting.wav --json -o result.json

Arguments

Argument Default Description
file required Audio file to transcribe (mp3, wav, m4a, ogg, flac, aac, webm). Max 50 MB, max 10 min.
--language / -l auto-detect BCP-47 language code (e.g. en, zh, ja). Omit to auto-detect.
--output / -o stdout Path to save transcript text (or JSON if --json is set).
--json off Output full JSON response with timestamps and speaker labels.
--api-key from env/config Noiz API key (overrides stored key).

Output Format

Without --json, only the transcript text is printed:

Hello, welcome to today's podcast. We have a special guest joining us...

With --json, the full structured response is printed:

{
  "language": "en",
  "transcript": "Hello, welcome to today's podcast...",
  "duration": 42.5,
  "segments": [
    {"text": "Hello, welcome to today's podcast.", "start": 0.0, "end": 3.2, "spk": 0},
    {"text": "We have a special guest joining us.", "start": 3.5, "end": 6.1, "spk": 0}
  ]
}

Supported Languages

Common codes: en (English), zh (Chinese), ja (Japanese), ko (Korean), es (Spanish), fr (French), de (German), pt (Portuguese), ru (Russian), ar (Arabic). Omit --language to auto-detect.

Configuration

# Save your API key once
python3 skills/speech-to-text/scripts/stt.py config --set-api-key YOUR_KEY

# Or set via environment variable
export NOIZ_API_KEY=YOUR_KEY

Get your API key at developers.noiz.ai.

Pricing

Billed at $0.0006 per second of audio. A 10-minute file costs ~$0.36. New accounts include 10,000 free TTS characters; STT is billed separately.

Security & data disclosure

  • Credential storage: API key is saved to ~/.config/noiz/apikey (permissions 0600). NOIZAPI_KEY env var is also supported.
  • Network calls: The audio file is uploaded to https://noiz.ai/v1/speech-to-text for transcription. No data is sent until you run the command.
  • File limits: Max 50 MB per file, max 10 minutes (600 seconds) of audio.

Requirements