Japanese audio to text test
Can AI Transcribe Japanese Business Audio Accurately?
We gave five tools the same 51-second recording with formal Japanese, prices, dates, API, CSV, and two mixed letter-number identifiers. Three returned transcripts. Only one preserved every operational detail.
We wrote and recorded the Japanese source ourselves, uploaded the same file, and checked each business value against the script. Product links on this page are direct links; we do not earn a commission from them yet.
A short business message with details that must not drift
The speaker introduced herself as Nakamura from the Sales Planning Department of Aoba Solutions. She referred to a quotation, confirmed a quantity and two prices, changed the delivery date, and requested a reply by 4:00 p.m.
管理番号A-2048、音声解析端末XR-205、数量48台、単価3万7,500円。
| Target detail | Intended value |
|---|---|
| Management number | A-2048 |
| Product model | XR-205 |
| Quantity | 48 units |
| Unit price | ¥37,500 |
| Total including tax | ¥1,980,000 |
| Original delivery date | October 6 |
| Revised delivery date | October 9 |
| Technical terms | API / CSV |
| Reply deadline | 4:00 p.m. today |
The tenth scored detail was the phrase stating that the API integration and CSV export specifications had not changed.
What each Japanese audio transcription tool returned
We counted an error as major when it changed a business value or meaning. Missing punctuation, hyphens, or preferred number formatting were documented but not counted as major when the underlying value remained clear.
| Tool | Status | Major errors | Identifier output | Native review |
|---|---|---|---|---|
| Notta | Completed | 0 major errors | A2048 / XR205 | All letters and digits were correct; both hyphens were omitted. |
| TurboScribe | Completed | 1 major error | A2048 / XR205 | Identifiers were readable, but 仕様 (specification) became 使用 (use). |
| Sonix | Completed | 2 major errors | A 248 / エックス 2005 | Both business-critical identifiers changed despite 95.83% displayed confidence. |
| Otter.ai | Not scored | No output | — | The Basic account had no lifetime file imports remaining. |
| JotMe web | Not scored | Processing failed | — | The public web converter accepted the file but did not return a transcript. |
Otter.ai and JotMe were not ranked for accuracy because neither produced a transcript in this run. A plan limit and a processing failure are useful workflow findings, but they are not recognition scores.
The transcript can look professional while the key detail is wrong
A-2048 → A 248
A management number lost a zero. The product model XR-205 also became エックス 2005. Both errors could send someone to the wrong record or item.
NOTTA
- Preserved all ten scored operational details
- Kept API and CSV correctly
- Kept the original and revised delivery dates
- Needed cleanup for hyphens, kanji numerals, and アオバ
OTHER RISKS
- TurboScribe changed 仕様 (specification) to 使用 (use)
- Sonix changed both mixed letter-number identifiers
- Sonix displayed 95.83% confidence despite those errors
- Two services returned no transcript to compare
The price, total, quantity, dates, and deadline were correct in all three completed outputs. That does not make the transcripts interchangeable: business identifiers and context-sensitive kanji were the harder parts.
How to use Japanese audio to text for business
- 1Upload the cleanest original file.
Avoid re-recording a call through a speaker when the original audio is available.
- 2Check every identifier first.
Compare model numbers, order numbers, names, dates, quantities, and prices with the audio or source document.
- 3Then check Japanese meaning.
Review kanji choices, corrections, polite phrasing, and words that sound alike.
- 4Do not trust formatting or confidence alone.
A clean transcript and a high confidence percentage can still hide operational errors.
Start with
NottaBest content result in this controlled business test, with every scored operational detail preserved.
Use for
First draftMeeting notes, internal summaries, and searchable records that a person will verify before use.
Always check
Critical dataNames, codes, quantities, prices, dates, deadlines, and context-sensitive Japanese wording.
What this result does—and does not—prove
This was one 51-second M4A recording, read by one native Japanese speaker in a quiet room. It is evidence about this specific workflow, not a universal accuracy percentage for every accent, microphone, or meeting.
Controlled
Same source file and Japanese language setting for every attempted service.
Native-reviewed
Important values and wording were checked manually against the written script.
Reproducible
We publish the target terms, observed outputs, scoring rule, and plan limitations.
We did not assign an accuracy score to a service that returned no text. We also did not count harmless formatting preferences as meaning-changing errors. Future tests should add longer meetings, more speakers, accents, and natural workplace noise.
Bottom line
Use AI for the first draft. Verify the details that make the message actionable.
Notta was the strongest starting point in this test, but even its output needed formatting and name cleanup. For business use, no transcript should be treated as final until identifiers, values, names, and Japanese wording are checked.
Try Notta for free ↗Direct link · No commission yetJapanese business transcription questions
Which AI tool was best for Japanese business audio in this test?
Notta produced the strongest content result in this 51-second recording. It preserved every operational value and the formal business wording, although it removed hyphens, used kanji numerals, and wrote 青葉 phonetically as アオバ.
Can AI transcription preserve Japanese model numbers and codes?
Sometimes, but the output still needs checking. Notta and TurboScribe kept the letters and digits in A-2048 and XR-205 while removing the hyphens. Sonix changed both identifiers in this test.
Does a high confidence score mean a Japanese transcript is correct?
No. Sonix displayed 95.83% confidence for this transcript, but A-2048 became A 248 and XR-205 became エックス 2005. Confidence is a model signal, not an independent accuracy check.
Were all five tools ranked for accuracy?
No. Three tools returned transcripts and could be compared. Otter.ai was blocked by the Basic plan's file-import limit, and the JotMe web converter failed during processing, so neither was scored for accuracy.
Published August 13, 2026 · Test performed August 10, 2026