assemblyai-transcriber
Transcribe audio files with speaker diarization (who speaks when). Supports 100+ languages, automatic language detection, and timestamps. Use for meetings, interviews, podcasts, or voice messages. Requires AssemblyAI API key.
Why use this skill?
Transcribe audio files into text with speaker identification, timestamps, and automatic language detection using the AssemblyAI Transcriber skill for OpenClaw.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/xenofex7/assemblyai-transcriberWhat This Skill Does
The assemblyai-transcriber is a powerful OpenClaw AI skill designed to convert spoken audio into precise, human-readable text. It leverages the robust AssemblyAI engine to provide high-accuracy transcriptions with support for over 100 languages. Beyond simple text conversion, this skill excels at speaker diarization—the process of identifying and labeling different speakers within an audio file (e.g., "Speaker A," "Speaker B"). It also extracts precise timestamps for every utterance, allowing you to easily map text to specific moments in a recording. With built-in automatic language detection and compatibility with major audio formats like MP3, WAV, and M4A, it is a versatile tool for any audio documentation task.
Installation
To integrate this skill into your environment, use the OpenClaw command line interface. First, ensure you have an active AssemblyAI API key from their official website. Run the command: clawhub install openclaw/skills/skills/xenofex7/assemblyai-transcriber. Once installed, secure your credentials by setting the ASSEMBLYAI_API_KEY environment variable or adding the key to your ~/.assemblyai_config.json file. This ensures the agent has the necessary authorization to process your audio files.
Use Cases
This skill is perfect for professional and personal workflows. For corporate environments, it is ideal for generating verbatim transcripts of board meetings, daily stand-ups, or client consultations. Content creators can use it to create accessibility captions for podcasts or YouTube videos. Researchers often utilize the speaker diarization feature for in-depth qualitative interviews, while students can leverage it to transcribe complex lectures or study sessions for easier review.
Example Prompts
- "Please transcribe the recording located at /home/user/downloads/interview_final.wav and generate a summary of the main points discussed."
- "Transcribe the podcast episode from this URL: https://example.com/podcast.mp3. Make sure to include speaker labels and timestamps in the output."
- "Run a transcript on meeting_notes.m4a. Ignore the speaker diarization; I just need a clean text body with no labels."
Tips & Limitations
For optimal results, ensure your audio recordings have minimal background noise, even though the engine handles noise filtering effectively. The diarization feature is most accurate when speakers have distinct voices and avoid talking over each other. If you are processing long files, note that costs accrue per minute after the initial 100-minute free tier. Always test with a short clip first to ensure the audio quality is sufficient for the detection model.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-xenofex7-assemblyai-transcriber": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: file-read, external-api, code-execution
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