Choosing a transcription tool when you are hard of hearing

Transcription tool comparisons all look alike. They rank on speed, on price, on the number of languages listed on the homepage.

Those are reasonable criteria when transcription is a convenience. They stop being adequate when it is the only way you find out what someone said to you. Here are the ones that matter in that case.

Why the usual comparisons miss

Someone transcribing for convenience can always replay the audio when the text looks doubtful. They have a safety net.

When you struggle to hear, that net does not exist. The text is not a convenience, it is the source. A transcription error is not an annoyance: it is false information with nothing to correct it, and every chance of being taken as true.

That reorders everything. Speed becomes secondary. Reliability, and above all the way a tool fails, becomes the whole question.

The six criteria that matter

1. Accuracy on the accents you actually receive. Not on a demo sample, but on the voices of your family and colleagues. Current models are excellent on standard speech and far more erratic on accents less represented in their training data. It is the most personal criterion here, and the only one no comparison can settle for you.

2. Behaviour in noise. This is where tools separate. A voice note recorded somewhere quiet transcribes acceptably almost anywhere. One recorded in the street tells the serious tools from the rest. Test with your worst messages, not your best.

3. Handling of long voice notes. Many tools cap out, truncate without warning, or degrade after a few minutes. Silent truncation is the worst possible failure here: you read a message that looks complete and is not.

4. Latency. It matters less than people assume for an asynchronous voice note, and enormously for live conversation. Separate the two needs, because they are not the same tools.

5. Speaker separation. Irrelevant on a one-to-one voice note. Decisive on a meeting or group recording, where a wall of text with no indication of who is speaking is often less useful than nothing.

6. What happens to your data. A service that transcribes server-side is sending your audio somewhere. The questions are simple and rarely asked: who processes the file, in which country, how long it is kept, and whether it trains a model.

The main families of tools

WhatsApp's built-in transcription. Free, integrated, processed on the device, which makes it the strongest option on privacy. It is also limited: availability varies by language and device, there are length constraints, and it gives you words rather than a summary. For plenty of short messages it is entirely sufficient, and it is often the right place to start. We covered its limits in a dedicated article.

Dictation and transcription apps. Powerful, often excellent on long files, with speaker separation and export. The cost is friction: install, create an account, export the voice note from WhatsApp, import it, wait. For a message that just arrived, that is a lot of steps.

Live transcription tools. Built for face-to-face conversation rather than messages. Valuable in a meeting, beside the point for an asynchronous voice note.

Bots inside the messenger. You forward the message, you get the text. Friction is minimal since nothing leaves the app. In exchange, processing happens server-side, which returns you to criterion 6.

Testing a tool in ten minutes

A simple protocol beats any comparison.

Take three of your real voice notes: one short and clean, one long, one recorded in noise. Run them through the tool. Read all three transcripts without replaying the audio, exactly as you would in real life.

Then check three things. Are the proper nouns and numbers right, since those carry the critical information. Does the tool flag its uncertainty, or assert everything with equal confidence, which is far more dangerous. And is the noisy one usable at all, or would you have had to listen anyway.

A tool that fails visibly is better than one that fails silently.

Where Abrège fits, honestly

We make Abrège, so here are the facts rather than a pitch.

What it does well: friction is minimal, you forward a voice note inside WhatsApp and get the text back, with no app and no account. It returns a summary alongside the transcript, which matters on long messages. The first five summaries each month are free, which is enough to test it on your own messages.

What it does less well, or not at all: transcription runs through OpenAI's API, the only step handled outside our servers. The audio is deleted afterwards with no copy kept, but if your requirement is that nothing leaves your phone, WhatsApp's built-in transcription is the right answer and we are not going to pretend otherwise. We do not separate speakers on a group recording. And past the free messages, it needs a subscription.

In short

When transcription is a convenience, you pick on speed and price. When it is your access to the conversation, pick on reliability under your real conditions: your contacts, your accents, your noisy voice notes.

Test with your worst messages, check the proper nouns and numbers, and be wary of a tool that never shows any doubt. The right answer may well be WhatsApp's free transcription.