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Faster Whisper

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by ThePlasmak Β· v1.5.1 Β· MITRepository

Local speech-to-text using faster-whisper β€” 4-6x faster than OpenAI Whisper with identical accuracy. GPU acceleration, SRT/VTT/TTML subtitles, speaker diarization, and chapter detection.

Install on your platform

We auto-selected Claude Code based on this skill’s supported platforms.

1

Run in terminal (recommended)

terminal
claude mcp add faster-whisper npx -- -y @trustedskills/faster-whisper
2

Or manually add to ~/.claude/settings.json

~/.claude/settings.json
{
  "mcpServers": {
    "faster-whisper": {
      "command": "npx",
      "args": [
        "-y",
        "@trustedskills/faster-whisper"
      ]
    }
  }
}

Requires Claude Code (claude CLI). Run claude --version to verify your install.

About This Skill

What it does

faster-whisper provides local speech-to-text transcription capabilities that are significantly faster – up to 6 times quicker – than the standard OpenAI Whisper model while maintaining comparable accuracy. It supports GPU acceleration for improved performance and offers features like SRT/VTT/TTML subtitle generation, speaker diarization (identifying different speakers), and automatic chapter detection within audio files. This allows for efficient transcription of long-form audio content without sacrificing quality.

When to use it

  • Transcribing lengthy lectures or presentations where speed is crucial.
  • Generating subtitles for videos in SRT, VTT, or TTML formats for accessibility or distribution.
  • Analyzing meeting recordings and identifying different speakers involved in the conversation.
  • Creating chapter markers within podcasts or audiobooks to improve navigation.

Key capabilities

  • GPU acceleration for faster transcription speeds
  • SRT/VTT/TTML subtitle generation
  • Speaker diarization
  • Chapter detection

Example prompts

  • "Transcribe this audio file and generate an SRT subtitle file."
  • "Identify the speakers in this meeting recording."
  • "Create chapter markers for this podcast episode based on pauses and content changes."

Tips & gotchas

  • A GPU is highly recommended to take full advantage of faster-whisper's speed improvements. Without a GPU, transcription will be slower.
  • The accuracy of speaker diarization can depend on audio quality and the clarity of different speakers’ voices.

Tags

Requirements

Required Binaries
python3
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Verified Commit1c8d6a68 β†’

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Details

Version
v1.5.1
License
MIT
Author
ThePlasmak
Installs
0

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Passed automated security scans.

Pinned commit1c8d6a68

Install command fetches the verified snapshot, not the live repository.