Best AI Note-Taking Apps for Non-English Meetings

Most "best AI note-taking app" lists are quietly written for English speakers. The tools showcased, the accuracy numbers cited, the features highlighted — all measured against English audio from North American and British speakers. If your team primarily works in Japanese, German, French, Spanish, or Korean, those rankings often tell you very little about how a tool will actually behave in your meetings.

This guide is written for multilingual remote workers and teams who need honest information. We looked at how each major tool performs across non-English languages — not just whether a language appears on a feature page.

---

Automate your meeting notes. MinuteKeep records your meeting and uses AI to transcribe, summarize, and extract action items. 9 languages, no subscription, 30 min free.

Why Non-English Transcription Is a Harder Problem

AI transcription works by training large models on vast amounts of audio paired with text. The more audio a model has seen for a given language, the better it performs. English has an enormous head start: decades of digitized media, podcasts, conference recordings, and training datasets. Most major languages don't come close.

This creates a practical gap that shows up in a few specific ways:

Accents and regional variation. Even when a tool supports German or Spanish, it may have trained primarily on standard high-resource accents (Hochdeutsch, Castilian Spanish). A Colombian speaker, a Bavarian speaker, or a Taiwanese Mandarin speaker may get noticeably worse results than the accuracy figures suggest.

Mixed-language meetings. Remote teams often code-switch — a Japanese team might discuss business in Japanese but use English product names, brand terms, or technical phrases mid-sentence. Tools that require you to select one language before the meeting begins will stumble every time someone switches.

Proper nouns and domain vocabulary. Company names, product names, people's names, and technical terms are already hard for AI to transcribe correctly. In non-English audio, the problem compounds: "Tanaka-san" might come through as "Tanaka-san," or it might not. Tools without custom dictionary support give you no way to fix systematic errors.

Character-based languages. Japanese, Chinese, Korean, and Arabic require the AI to work with fundamentally different scripts. Character error rate, not word error rate, is the right accuracy metric — and most published benchmarks only report word error rate for alphabetic languages.

For a deeper look at how multilingual transcription technology actually works, see our guide to multilingual AI transcription.

---

The Apps, Evaluated for Non-English Performance

Notta

Notta is the tool most often recommended for non-English meeting transcription, and the language coverage is genuinely broad — 58 languages for transcription, with bilingual mode supported for 11 language pairs.

In practice, Notta works well for high-resource languages. Japanese, German, French, Spanish, and Portuguese all perform reasonably in clean recording conditions. The app can auto-detect the spoken language, which matters for teams that don't want to manually configure language settings before every call.

The limits appear in two areas. First, automatic language detection does not extend to mixed-language conversations — if you switch between languages mid-meeting, detection can lag or fail. Second, user reports (including G2 reviews as of early 2026) flag accuracy problems with some mid-tier languages: Greek and Portuguese have received specific criticism, and accuracy in noisy environments drops more steeply than the headline 98.86% figure implies.

Pricing: Free tier (limited minutes). Pro around $13.99/month. Business from $27.99/user/month.

Non-English verdict: Strong for single-language meetings in major world languages. Less reliable in code-switching meetings or noisy environments.

---

Otter.ai

Otter.ai supports five languages: English (US and UK), Japanese, Spanish, and French. That's it.

The limitation is real and meaningful. If your team works in German, Korean, Portuguese, Arabic, or Chinese, Otter is not a viable option. The tool does not have a roadmap commitment on its help pages for additional language support, and the recent expansion to Japanese and Spanish only added two languages while competitors moved to 30-60.

For the languages it does support, Otter's transcription is solid — particularly for English, where it has invested the most model training. Japanese transcription is functional but has received mixed reviews for accuracy with fast speakers or heavy use of technical vocabulary.

Otter's real value proposition is its real-time collaborative transcript and tight integration with Zoom, Google Meet, and Teams. If your meetings happen in one of its five supported languages and you want a tool your whole team can annotate in real time, Otter is worth considering. For multilingual teams, it's not the right fit.

Pricing: Free (300 min/month), Pro $8.33/month billed annually (1,200 min/month), Business $20/user/month (6,000 min/month).

Non-English verdict: Only viable if your meeting language is Japanese, Spanish, or French. No German, Korean, Chinese, Arabic, or Portuguese support.

---

Fireflies.ai

Fireflies.ai claims support for over 60 languages and in some sources has been listed as supporting over 100. The language breadth is real — Fireflies uses a combination of underlying transcription engines and has invested in broader coverage than most competitors.

The practical limitation is that Fireflies lacks automatic language detection. You need to select the meeting language in advance. For a team that always meets in the same language, this is a minor friction. For multilingual calls, it creates a structural problem: one wrong selection at the start means a transcript that may be partially or entirely unusable.

Fireflies is primarily designed as an enterprise team tool. It joins your calls via a bot (visible to all participants), syncs to CRM tools like Salesforce, and is built around the idea that meeting data belongs to the organization. For individual professionals or small teams who want to record discretely without announcing an AI bot, this design is a poor fit.

Non-English accuracy with Fireflies has been reported as strong for major European languages and Japanese. CRM-heavy enterprise teams working in French, German, or Spanish may find it works well for their structure.

Pricing: Free plan (limited AI credits), Pro $10/user/month annually, Business $19/user/month, Enterprise $39/user/month.

Non-English verdict: Broad language coverage, but requires language pre-selection. Bot-join model adds friction for discreet recording scenarios.

---

tl;dv

tl;dv supports transcription in over 40 languages with automatic language detection — a meaningful advantage for multilingual teams. It distinguishes itself by supporting regional dialects within languages, which is rare. A Spanish speaker from Mexico and one from Spain should both get reasonable results without requiring separate configuration.

The tool is designed primarily around video call recordings (Zoom, Google Meet, Teams), and the mobile experience is limited. If your meetings happen in-person, over a phone call, or in any context outside those three platforms, tl;dv's coverage gaps become relevant.

Accuracy for non-English content is competitive with other Whisper-based tools (tl;dv uses OpenAI's Whisper model as its transcription backbone), and the dialect-aware design helps at the edges. The free tier is functional but limited; the Pro plan is $20/user/month.

Non-English verdict: Best automatic language detection among the major tools. Dialect support is a genuine differentiator. Limited to video call platforms.

---

Google Meet and Microsoft Teams (Built-In)

Both platforms now include built-in transcription, which sounds convenient until you look at language support.

Google Meet's native transcription supports five languages: English, Spanish, Portuguese, French, and German. Notably absent: Japanese, Korean, Chinese, Arabic. And this feature requires Business Standard plan or above ($14/user/month), which means it is not accessible on free or starter workspace plans.

Microsoft Teams' built-in transcription focuses on English and a handful of major European languages. For Japanese, Korean, Chinese, or Arabic teams, the native transcription is not a viable solution. Microsoft Copilot adds more language capability but again requires specific licensing tiers.

For teams already paying for these platforms at appropriate tiers, the built-in tools are convenient for English meetings. For non-English teams, or anyone outside the small supported language set, they fall short.

Non-English verdict: Too narrow for most multilingual teams. Best treated as a convenience feature for English-primary organizations.

---

MinuteKeep

MinuteKeep is an iOS app built on OpenAI's Whisper transcription model and GPT-4.1 for summarization. It supports 9 languages: English, Japanese, Korean, German, French, Spanish, Portuguese, Arabic, and Chinese.

A few design decisions make it specifically useful for non-English users.

Cross-language summarization. You can speak in Japanese and receive your summary in English — or any other supported language. This is practical for multilingual professionals who want to share meeting notes with colleagues who work in a different language. You don't need a separate translation step.

Custom dictionary. You can add company names, product names, people's names, and technical terms to a dictionary that the app uses to improve transcription. For non-English content in particular — where proper nouns are where AI most often fails — this is a significant quality improvement. An article on using custom dictionaries effectively covers this in more detail.

No bot, no account. Recording happens directly on your iPhone, without a bot joining your call and without creating an account. For professionals in Japan, Korea, or Germany where attitudes toward meeting recording vary by workplace culture, the ability to record privately matters.

Pricing is usage-based, not a subscription. The app includes 30 minutes free on install. Additional time packs: 2 hours for $0.99, 7 hours for $2.99, 18 hours for $6.99. Time packs never expire.

The limitation: MinuteKeep is iOS only and has no real-time live transcription during calls. You record the meeting and the transcription processes after. For the best iPhone meeting transcription apps overall, it ranks well — but if you need a live, in-meeting transcript on other platforms, it is not designed for that use case.

Non-English verdict: Well-suited for multilingual professionals who need offline-capable, private recording with cross-language summarization. Custom dictionary meaningfully improves accuracy for proper nouns.

Download MinuteKeep on the App Store

---

Language Support Comparison Table

App	Languages	Auto-Detect	Mixed Language	Custom Dictionary	Bot Required
MinuteKeep	9 (EN, JA, KO, DE, FR, ES, PT, AR, ZH)	Yes	Partial	Yes	No
Notta	58	Yes	Limited	No	No
tl;dv	40+	Yes	Limited	No	Yes (video calls)
Fireflies.ai	60+	No	No	No	Yes
Otter.ai	5 (EN, JA, ES, FR)	No	EN+FR only	No	Yes (video calls)
Google Meet	5 (EN, ES, PT, FR, DE)	No	No	No	N/A (built-in)
Microsoft Teams	Limited (EN-primary)	No	No	No	N/A (built-in)

---

Tips for Improving Non-English Transcription Accuracy

Regardless of which tool you choose, these practices consistently improve results for non-English audio.

Record in a quiet environment. Background noise hurts transcription accuracy in any language, but non-English models have smaller error-recovery margins because they have seen less training data. A quiet room helps disproportionately.

Speak at a moderate pace. Fast speech is harder for AI to parse in all languages. In Japanese and Korean, where pitch accent and context-dependent pronunciation affect word segmentation, a deliberate pace makes a meaningful difference.

Use a dedicated microphone when possible. The built-in microphone on a phone in a conference room pickup pattern is one of the most challenging inputs for any transcription model. Even an inexpensive clip-on microphone improves audio quality substantially.

Add proper nouns to a custom dictionary. If your tool supports it — MinuteKeep does — populate the dictionary before your first important meeting. Your company name, project names, key people, and technical terms should all be in there. You'll catch errors before they appear rather than correcting them in every transcript.

Select the dominant language, not a secondary one. If your meeting is 80% Japanese and 20% English product terms, set the language to Japanese. The English terms will often transcribe correctly anyway; setting the language wrong will cause the majority content to fail.

Break up very long recordings. For in-person meetings longer than two hours, consider stopping and restarting the recording at natural breaks. Shorter audio files process more reliably than very long ones, and errors in long recordings can cascade if the model loses context.

---

FAQ

Can AI transcription apps handle meetings with multiple languages in the same conversation?

Some can, but it is one of the harder problems in transcription. Tools with automatic language detection (tl;dv, Notta, MinuteKeep) handle it better than those requiring pre-selection (Fireflies, Otter). No current tool handles frequent mid-sentence code-switching flawlessly — the best you can expect is that the dominant language transcribes accurately, with English technical terms usually surviving the process intact.

Is OpenAI Whisper good for non-English transcription?

Whisper was trained on 680,000 hours of audio across 99 languages, which makes it significantly broader than most proprietary transcription models. For Japanese, German, French, Spanish, Korean, Arabic, and Chinese, Whisper generally outperforms alternatives. It supports 99 languages and achieves word error rates below 10% for major world languages in clean audio conditions. Apps built on Whisper — including MinuteKeep — inherit these multilingual strengths.

Why is German transcription harder than French or Spanish?

German's compound words, grammatical case endings, and regional dialect variation create more transcription challenges than languages with simpler morphology. An AI model hears "Qualitätssicherungsmaßnahmen" and must segment it correctly while also handling speaker accent and sentence context. High-quality German transcription requires models that have seen substantial German training data — not all apps have invested equally here.

Does language support differ between transcription and summarization?

Yes, and this distinction matters. A tool might transcribe 58 languages but only summarize in English. MinuteKeep separates these clearly: transcription supports all 9 languages, and the summarization output language can be set independently — so you can transcribe Japanese audio and get an English summary. Notta and Fireflies handle summarization primarily in English even when transcribing other languages.

What is the best option for a team that conducts meetings in Japanese?

For Japanese specifically, MinuteKeep, Notta, and Otter.ai have all invested in Japanese transcription. MinuteKeep has the advantage of cross-language summary output and custom dictionary support, with no bot and no subscription. Notta has broader coverage for teams with meetings in other languages. Otter supports Japanese but lacks the customization features. Fireflies and tl;dv also support Japanese, with the caveat that both require a bot to join video calls.

---

Key Takeaways

• Most AI transcription tools were built for English first. Language coverage claims often overstate real-world non-English accuracy, especially in noisy environments or with regional accents.
• Otter.ai supports only 5 languages — not a viable choice for teams working in German, Korean, Chinese, Arabic, or Portuguese.
• Google Meet and Microsoft Teams built-in transcription cover only a handful of languages and require paid workspace tiers.
• Notta and Fireflies offer the broadest language coverage (58 and 60+ respectively), but neither has automatic mixed-language detection.
• tl;dv offers 40+ languages with automatic language detection and dialect awareness, limited to video call platforms.
• MinuteKeep offers 9 carefully supported languages with cross-language summarization, custom dictionary, no-bot recording, and no subscription. Best for iOS users who need private, flexible multilingual transcription.
• Regardless of tool: quiet recording environment, moderate speaking pace, and a populated custom dictionary meaningfully improve non-English accuracy.