How accurate is Amharic transcription?
Amharic has less training data in Whisper, so accuracy depends heavily on the recording. Use Best where possible and treat the result as a first draft.
- Language
- Amharic (አማርኛ)
- Accuracy estimate
- Variable
- Suggested setting
- Best
- Writing system
- Ge'ez
- Translate into English
- Built in
- Subtitles
- SRT and VTT with line rules
Estimate based on the per-language error rates OpenAI published for Whisper in OpenAI’s Whisper repository. Recording quality matters more than anything else.
Tips for better Amharic transcripts
- Choose Amharic in the language menu rather than automatic detection. It helps most on short clips and recordings that start with music.
- Amharic is spoken in Ethiopia. Regional accents are handled well; the Best setting gives the most consistent results across them.
What people transcribe in Amharic
Common uses include video files, sermons, subtitles, user research, club and community meetings. Because nothing is uploaded, it also suits confidential interviews and internal meetings.
Need it in English? Translate Amharic audio into English in one step, with timestamps.
Writing Amharic: what to expect in the transcript
Whisper writes Amharic in standard spelling and punctuation. Names of people, brands and places are the most common errors. Fix one occurrence, then use Find and replace for the rest, or add it to your corrections list so future transcripts are fixed automatically.
If the speakers switch between Amharic and another language, choose Amharic manually instead of automatic detection. Automatic detection can be misled by a recording that opens in another language or with music.
Step by step: from recording to finished transcript
- Check the recording. Speech close to the microphone with little background noise gives the best result for Amharic. You do not need to convert it first; most audio and video files open as they are.
- Choose the spoken language, or leave automatic detection on if the whole recording is in one language.
- Pick an accuracy setting. Balanced suits clear speech; Accurate is better for interviews, accents and names.
- Add the file. Keep the tab open while it works; you can use other tabs and apps. Long recordings are processed in chunks, and finished text appears as it goes.
- Proofread with the audio. Click any timestamp to hear that line, use the speed control to slow down fast speech, and use Find and replace for repeated names.
- If there is more than one voice, turn on Speakers, set the speaker for each line, then type their names in the side panel. Names carry into every export.
- Export. Word and PDF for documents, TXT for plain text, SRT or VTT for subtitles, CSV or JSON for analysis.
Which accuracy setting to choose for Amharic
The speech model runs on your own device, so it is downloaded once and then saved in your browser. The app tells you the size before anything downloads, and it never downloads again unless you clear your browser data. For English, Balanced is usually enough. For most other languages, Accurate makes far fewer mistakes, and the app switches to it when you choose such a language.
| Setting | Model | One-time download | Best for |
|---|---|---|---|
| Fast | Whisper tiny | 64 MB | Quick drafts, phones, mobile data |
| Balanced | Whisper base | 136 MB | Clear speech and most everyday recordings |
| Accurate | Whisper small | 510 to 590 MB | Interviews, accents, names, most languages other than English |
| Best | Whisper large-v3-turbo | About 760 MB | Difficult audio; needs a computer with graphics acceleration |
On mobile data the app suggests Fast automatically. On a laptop with Wi-Fi, Balanced is the default and Accurate is worth the extra download if you transcribe Amharic regularly. You can switch settings at any time; each model is downloaded only the first time you use it.
Which file to download
| Format | Use it for |
|---|---|
| Word (DOCX) | Formatted transcript with speakers and optional timestamps. Opens in Word, Google Docs and Pages. |
| A fixed copy for sharing or filing. Uses your browser’s print dialog, so you can choose paper size. | |
| TXT | Plain text, with or without timestamps, for notes, email or other tools. |
| SRT and VTT | Subtitle files timed to the audio, for video editors and players. |
| Markdown | Headings and timestamps for note apps such as Obsidian and Notion. |
| CSV | One row per line with start, end, speaker and text, for spreadsheets and qualitative analysis. |
| JSON | Every segment with exact timings, for developers. |
Fixing common problems
- The file will not open
- Most audio and video formats open directly. If a file is rejected, it usually uses a codec your browser cannot decode, such as some MKV or AVI files. Open it in a free converter or in the app that recorded it and save it as MP3, M4A or MP4. The file formats page lists what opens where.
- It is slower than expected
- Speed depends on your device and the accuracy setting. Chrome and Edge on a laptop with graphics acceleration are fastest. Plug in a laptop on battery, close heavy tabs, or choose a smaller setting. Phones work, but long files are faster on a computer.
- The wrong language was detected
- Automatic detection can be misled by music or a different language at the start. Choose Amharic manually and run the file again.
- Repeated lines or text during silence
- Speech models can invent text during long silences or music. The app skips silent stretches and removes repeated lines, and Clean up audio helps further. If it still happens, try the Accurate setting.
- The browser ran out of memory
- Very long recordings on devices with little memory can hit the browser’s limit. Use Fast or Balanced, close other tabs, or split the recording into parts. A desktop or laptop handles several hours.
- The model download stopped
- Check your connection and try again. Model files that finished downloading are kept, so a second attempt is quicker. Once the model is saved, no connection is needed.
What happens to your Amharic recording
Your browser reads the file from your device and runs the speech model locally. The audio, the video and the transcript are never sent to a server, so there is nothing for us, or anyone else, to store, train on or lose in a breach. Finished transcripts are saved only in your browser’s storage, where you can export or delete them in your library. The only thing that comes from the internet is the speech model itself, once. You can check this by turning off Wi-Fi after the first transcript: it keeps working.