Dictation or Transcription? Speaking Text Live vs Converting a Recording

Two jobs that look similar

Both turn speech into text with a speech recognizer, which is why the terms get blurred. The difference is in who the speaker is talking to and when the text appears.

When you dictate, you are composing. You speak a sentence, watch it appear, fix a misheard word and carry on. The speech is aimed at the software, and you adapt how you talk to get good text: clear, a little slower, with pauses at the ends of sentences.

When you transcribe, the speech already happened. It might be a meeting, a lecture, an interview or a voice memo recorded on a walk. Nobody was talking to the software, so the text has to capture natural speech with its hesitations, overlaps and false starts. You check and correct it afterwards. The explanation of how speech to text works covers the shared recognition step; this page is about the two workflows around it.

There is also a hybrid with a long history in law and medicine: a professional dictates into a recorder, and someone else, now often software, transcribes the recording later. It uses dictation's deliberate speaking style with transcription's after-the-fact timing.

How each workflow runs

Dictation

Speak into an app; text appears within a second or two; you correct on screen as you go.

Transcription

Record first; upload or open the file later; receive the full text; proofread against the audio.

Speakers

Dictation: almost always one person. Transcription: one or many.

Feedback

Dictation: immediate. Transcription: only after processing.

Output

Dictation: a document in progress. Transcription: a transcript, often with timestamps or subtitle files.

Dictation tools include the voice typing built into phone keyboards, desktop operating systems and word processors, plus dedicated dictation software used in some professions. Transcription tools accept audio or video files and return text, sometimes with timestamps and subtitle files.

Punctuation and editing commands

Dictation software usually lets you speak punctuation and formatting: "comma", "full stop" or "period", "new line", "new paragraph", "question mark". Many tools also accept editing commands such as deleting the last phrase or selecting a word, and some add punctuation automatically from your phrasing. The exact command set varies by app, language and platform, so check the help pages for the tool you use.

Transcription works differently. The speakers in a recording were not giving commands, so a transcription engine predicts punctuation and capitalization from pauses, intonation and context. That makes punctuation in transcripts generally good but imperfect, especially in fast or run-on speech. Saying "comma" into a recording you plan to transcribe is not a reliable way to get a comma: the word may simply appear in the text.

What drives accuracy in each

Dictation has built-in advantages. One speaker, close to the microphone, speaking deliberately in a quiet room is close to ideal input. Some dictation software can learn your voice or accept a custom word list, and you fix errors while the context is fresh.

Live recognition also has a constraint: it must show text before you finish speaking. Streaming recognizers commit to words with limited look-ahead and sometimes revise them a moment later, which is why dictated text can flicker as you talk.

Transcription faces harder audio but has more context. It works on recordings where people speak naturally, interrupt each other, sit far from the microphone or talk over background noise. On the other hand, a file-based engine can analyze each stretch of audio with the words on both sides available, which helps with ambiguous phrases. The quality of the recording decides most of the result; speaking clearly for transcription covers what speakers can do to help.

• Dictation suffers when you speak in long unbroken streams, mumble, or use unusual names the software has never seen.
• Transcription suffers with distant microphones, room echo, crosstalk, music under speech and heavy accents the model handles less well.
• Both struggle with jargon, rare names and numbers, so plan to check those.

Privacy considerations

Privacy depends on where recognition runs, and that differs by tool and setting. Some phone and desktop dictation features process speech on the device for supported languages; others send audio to a cloud service. Settings and defaults change between versions, so check your device's documentation if it matters. The trade-offs are discussed in on-device speech AI.

Transcription services usually receive the recording or parts of it. Before uploading sensitive recordings, check how long the service keeps audio and results, whether it uses them for training, and what consent the people in the recording gave. For workplace, legal, medical or research material, follow your organization's own policies.

Which tasks suit each

• Drafting emails, notes, essays and reports: dictation. You stay in control of every sentence.
• Reducing typing because of injury, fatigue or a motor disability: dictation, often combined with voice control of the computer.
• Capturing ideas while walking or driving, when you cannot watch a screen: record a voice memo and transcribe it later.
• Meetings, interviews, focus groups and lectures: transcription. Nobody should have to perform for the software.
• Subtitles for a video: transcription, because you need timestamps tied to the recording.
• Quoting someone accurately: transcription of the recording, checked against the audio.

In language teaching, dictation means something else again: a listening exercise where learners write down what they hear. That use is covered in dictation practice with transcripts.

Mistakes and limits of each approach

• Expecting dictation to work for a conversation. It is built for one speaker addressing the software and tends to mangle back-and-forth talk.
• Speaking dictation commands into a recording. They end up as words to delete, or as unpredictable punctuation.
• Skipping the proofread. Both methods produce errors that read fluently, so a wrong word can look right. The guide to proofreading an AI transcript applies to dictated drafts as well.
• Treating spoken drafts as finished writing. Speech is looser than prose; dictated text usually needs tightening.
• Assuming dictation is private because it feels local. Check where your tool processes audio.

Where mydubly fits: recorded files only

mydubly is a transcription tool, not a dictation tool. It works on recorded files you choose from your device: audio as MP3, WAV, M4A, AAC, OGG or FLAC, and video as MP4, MOV, WebM, MKV or M4V, up to two hours per file. There is no live mode, no microphone dictation, no spoken command vocabulary and no native app or API.

Upload a recording to the audio to text tool and the browser decodes it locally, splits it into chunks of about 30 seconds and sends compressed audio over HTTPS for recognition with Whisper, which detects the spoken language automatically. You get a plain transcript, a timestamped transcript with [m:ss] labels, and SRT and VTT subtitles. Speakers are not labeled. Keep the tab open until the job finishes; closing it cancels the job.

The cost is 1 credit per minute with a 5-credit minimum, so a 12-minute voice memo costs 12 credits (1.2¢). Uploaded audio chunks and results are deleted within 30 minutes of the job finishing. For the walking-and-talking case, the voice memo to text page describes the workflow from phone recording to transcript.

Next step

Pick by situation: dictate when you are writing and can watch the screen, record and transcribe when you are talking with people or cannot stop to correct. If you already have a recording, transcribe it and proofread the names, numbers and quotes before you use the text.