Voice typing: write into a text field
The starting point is something you want to write. You place a cursor in an email, document or prompt, speak your words and use the result as a draft. The useful output is text in the right place, with a chance to review it before sending.
Choose this workflow when you are the author and prefer speaking some of the draft to typing it. Whispek’s voice input is built around this job.
Transcription: turn speech into a text record
The starting point is speech you want represented in writing, which might be a recording, an interview or a dictated note. Depending on the tool, you may need timestamps, speaker labels, file import or a verbatim transcript.
Those are separate capabilities. The presence of speech recognition does not establish that an app includes all of them. Whispek’s voice typing pages do not claim meeting bots, speaker diarization or general audio-file transcription.
Text cleanup: prepare spoken wording for reading
A spoken passage can include repetition and corrections. Cleanup can make the result easier to read, but it can also change wording. It suits a draft you will review, rather than a record that must preserve exactly what was said.
The current Whispek desktop workflow includes cleanup after recognition. This comparison describes different tasks; it does not mean the app provides a transcription-only mode or a guaranteed verbatim transcript.
Pick by the output you need
- Email or message draft: start with voice typing.
- Ideas for a document: dictate short passages and edit them in your writing app.
- An answer or rewrite based on a request: use an assistant workflow.
- A record requiring timestamps, speakers or exact wording: verify those requirements with a dedicated transcription tool.
- Sensitive material: check processing and retention requirements before choosing any service.
A simple decision
Ask: “Am I trying to write something, or preserve a record of something?” For writing, focus on text delivery, editing and vocabulary. For a record, focus on source fidelity, required metadata and how the audio is handled. That distinction is more useful than choosing by a broad “AI transcription” label.