Upload Japanese audio or video and get a transcript that picks the right kanji from context, preserves keigo verb forms, and handles the mix of kanji, hiragana, and katakana that makes Japanese transcription uniquely difficult.
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Japanese is written in three scripts simultaneously, where a single spoken word like 'hashi' could be 箸 (chopsticks), 橋 (bridge), or 端 (edge) depending on pitch accent and context. Keigo doesn't just add politeness markers — it replaces entire verb stems (いる→いらっしゃる, 食べる→召し上がる). Sentence-final particles like よ, ね, and な carry critical pragmatic meaning that changes how a statement should be read. Vocova's AI navigates all of this, producing transcripts that a native reader would find natural.
Drag and drop or select a file containing Japanese speech. Supports everything from podcast recordings to anime episodes to boardroom meetings.
The engine identifies word boundaries in continuous speech, selects the appropriate kanji versus kana rendering, and captures keigo levels and sentence-final particles that shape the meaning of each utterance.
Review the transcript with correct script mixing, edit inline if needed, and export for subtitles, translation, or documentation.
When the audio says 'kiku,' the AI determines whether to write 聞く (listen), 菊 (chrysanthemum), or 効く (take effect) based on the surrounding sentence. This is the core challenge of Japanese transcription — the same sound maps to dozens of possible characters — and Vocova resolves it through contextual analysis rather than defaulting to the most common option.
Japanese honorific speech doesn't just add a prefix — it transforms verbs entirely. する becomes なさる (respectful) or いたす (humble). 行く becomes いらっしゃる or 参る. The AI tracks the formality register of each speaker and outputs the correct morphological form, so business recordings read with the appropriate level of politeness intact.
Particles like よ (assertion), ね (seeking agreement), な (self-reflection), and かな (wondering) appear at the end of Japanese sentences and carry meaning that changes interpretation. The AI captures these rather than dropping them, which is critical for interview transcripts, dialogue, and any content where speaker attitude matters.
Japanese pitch accent distinguishes words that are otherwise identical in writing: 雨 (rain, pitch pattern A) vs 飴 (candy, pitch pattern B), 箸 (chopsticks) vs 橋 (bridge). While standard transcription engines often ignore pitch accent entirely, Vocova uses acoustic and contextual cues together to pick the intended word.
Native Japanese text freely mixes kanji (漢字), hiragana (ひらがな), and katakana (カタカナ) within a single sentence. Foreign loanwords should be in katakana, grammatical particles in hiragana, and content words in their conventional kanji-or-kana form. The AI reproduces this natural mixing pattern rather than outputting everything in one script.
Transcribe the Japanese audio first, then translate the transcript into English or 140+ other languages in one click. The Japanese source and the translation stay aligned segment by segment, so you can verify any line against what was actually said — including where keigo nuance has no direct English equivalent.
Character dialogue in anime uses distinctive speech patterns — masculine だ-form, feminine わ-endings, archaic でござる — that generic engines often garble. Get transcripts that reflect how characters actually speak, useful for fan translation, language study, and media analysis.
Business Japanese relies heavily on keigo, where misrepresenting a humble form as a respectful one changes who did what. The transcript preserves these distinctions so your meeting minutes reflect the actual social dynamics of the conversation.
Learners need transcripts that use kanji at the level a native would, not all-hiragana output that's easy for the engine but useless for study. See natural kanji usage alongside the audio to build reading ability.
Export as SRT or VTT with timing aligned to Japanese speech rhythm. The engine handles the fact that Japanese packs more semantic content per syllable than English, so subtitle segments are timed to natural phrase boundaries.
Academic interviews in Japanese often shift between polite and casual registers as rapport builds. The transcript captures these register shifts accurately so sociolinguistic and qualitative researchers can analyze the conversation as it actually occurred.
Get transcripts with natural kanji usage to study alongside audio. See how spoken Japanese maps to written form, including particles and verb conjugations that textbooks simplify.
Start with a Japanese transcript that correctly distinguishes keigo levels and homophones, reducing the disambiguation work that makes Japanese-to-English translation slow.
Transcribe anime, drama, and variety show dialogue with character-appropriate speech patterns preserved for subtitling, dubbing scripts, and content documentation.
Capture meetings conducted in Japanese with keigo levels intact. Share accurate records where the formality distinctions that matter in Japanese business culture are preserved.
Vocova outputs kanji where a native writer would use them. When you say 'kikan,' the AI determines from context whether to write 期間 (period), 機関 (institution), 帰還 (return), or 気管 (trachea) rather than falling back to きかん. This context-driven kanji selection is the most important quality marker for Japanese transcription.
Real Japanese conversations regularly shift between registers — a manager might use 丁寧語 with a client and switch to casual speech with a subordinate. The AI tracks each speaker's register independently and outputs the verb forms actually used, so おっしゃいました and 言ってた can coexist in the same transcript when that's what was spoken.
Yes. These particles are semantically meaningful in Japanese — そうですね (agreement-seeking) means something different from そうですよ (asserting). The AI treats them as part of the utterance, not noise to be trimmed. This matters especially for interview transcripts and dialogue where speaker stance is important.
The AI handles common dialect features like Kansai-ben's ～へん (negative), ～やねん (explanatory), and おおきに (thanks), as well as Tohoku and Kyushu speech patterns. It transcribes dialect forms as spoken rather than normalizing everything to standard Tokyo Japanese, though very heavy dialect may occasionally need minor edits.
Yes. English and other foreign loanwords are rendered in katakana following standard conventions — コンピューター, not こんぴゅーたー. The AI also handles recent loanwords and IT terminology that may not appear in traditional dictionaries, like サブスク (subscription) or リスケ (reschedule).
Japanese has extreme homophony — 'koushou' alone maps to 交渉 (negotiation), 考証 (investigation), 公称 (official name), 高尚 (noble), and more. The AI uses the full sentence context and topic domain to select the right characters. Accuracy is highest when the audio is clear and the surrounding context provides strong disambiguation cues.
Yes. Casual Japanese features heavy contraction — ている→てる, ～ではない→～じゃない, それは→そりゃ — and the AI reconstructs these contracted forms into readable text. It handles the rapid pace of variety show banter and casual conversation without losing content.
Yes. After transcription, use the built-in translation to convert the transcript into English or 140+ other languages. The Japanese source stays aligned with the English translation segment by segment — useful for subtitles, study notes, and sharing Japanese interviews or videos with readers who don't speak Japanese.
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