Whisper Transcription

Whisper Transcription

Overview

Use this umbrella for audio transcription tasks regardless of whether the runtime is local Whisper or the OpenAI API.

Choose a Path

• Local CLI: when you want offline transcription and already have the Whisper binary.
• OpenAI API: when you want hosted transcription, JSON output, or proxy-compatible API access.

Workflow

1. Identify the source audio format and desired output (txt, srt, json).
2. Pick local or API based on latency, privacy, and environment constraints.
3. Set model/language/prompt hints only when they improve the transcript.
4. Verify the transcript against the audio length and obvious speaker names.

References

• references/path-selection.md for runtime choice and output-format notes.

Pitfalls

• Don’t keep separate skills for local and API Whisper when the task class is identical.
• Don’t overfit model choice; prefer the simplest path that meets quality needs.
• Don’t forget to specify output format and destination.