Danish ka Finnish ntụgharị
DA FI
Ọnụọgụgụ
API dịnụ
Olee otú ịsụgharị Danish ka Finnish
1
Tinye ngwe gị
Tinye mọọbụ pịa ngwe gị Danish n'ime igbe ntinye aka n'elu. I nwere ike ịbanye ruo akara 10,000, mọọbụ ibubata faịlụ dọkumenti.
2
Pịa tụgharịa
Pịa bọtịnụ tụgharịa ma ọ bụ nọrọ n'ebe ahụ - ntụgharị n'onwe gị ga-amalite mgbe ịkwụsịla ịgụ. AI na-arụ ọrụ na ngwe gị n'ime millisekọnd.
3
Debata nsụgharị gị
Nsụgharị Finnish gị ga-apụta n'oge ọbụla. Pịa bọtịn ndebata ka ịdebata ya na klọbbụịlụ gị, mọọbụ tinye ya site na API anyị.
Asụsụ ndị a na-ejikarị Danish
Pịa okwu ọbụla iji tụgharịa ya n'oge ọbụla.
Ntụgharị nkịtị
Nweta Danish ka Finnish ntụgharị n'ime millisekọnd.
Nnyemaka dọkumenti
Wepụ Word, PDF, SRT subtitle na ndị ọzọ maka ntụgharị batch.
Ikikere API
Tinye nsụgharị abụọ a n'ime usoroiheomume gị na REST API anyị.
Danish ka Finnish API
Tinye nsụgharị abụọ a na usoroiheomume gị site n'ịkpọ API dị mfe.
Gosi dọkumenti API Nweta kii APIcurl -X POST https://api.translateapi.ai/api/v1/translate/ \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"text": "Hello", "source_language": "da", "target_language": "fi"}'N'ihe banyere Danish ka Finnish ntụgharị
TranslateAPI na-enye ngwa ngwa na ziri ezi Danish ka Finnish nsụgharị na-arụ ọrụ site na AI. Anyị ọrụ na-akwado:
- Ntụgharị ngwe - Gbanwee ngwe ọbụla ruo 10,000 akara n'oge na-adịghị anya
- Dọkumenti ọfụụ - Bubata faịlụ Word, PDF, na faịlụ ngwe maka ntụgharị
- Nnyemaka API - Tinye Danish ka Finnish ntụgharị n'ime usoroiheomume gị
- Báà - Gbanwee ngwe ndị dị iche iche n'ime arịrịọ ọfụụ
Jiri ihenhọrọ ndị ahụ
- Bagharịa Danish dọkumenti ka Finnish maka ọrụ
- Wepụ webụsaịtị na usoroiheomume site na Danish gaa Finnish
- Banye subtitle Danish na Finnish
- Kpọtụrụ na Finnish ndịna-ekwuo
Ntụgharị
- Òtù
- Danish (
da) - Target
- Finnish (
fi)
Ajụjụ ndị a na-ajụkarị
Turkic and Uralic languages stack many suffixes on a single root to express meanings that English splits across multiple words ("evlerimden" = "from my houses"). Danish to Finnish segments the agglutinative source word, translates each morpheme contextually, and reassembles the output in the target convention.
Yes — when the target language uses vowel harmony, the model emits suffixes that match the harmony class of the stem. Turkish front/back and rounded/unrounded harmony, Finnish front/back, and Hungarian front-rounded all round-trip correctly.
Finnish has 15 grammatical cases, Hungarian has 18+, Turkish 6 — most more than any Indo-European language. The model emits the correct case suffix for each output noun based on the semantic role in the target sentence.
Turkic and Uralic languages mark definiteness through case suffixes or word order rather than articles. The model handles this on output and respects definiteness in the source.
Yes — Turkish siz (formal), Hungarian Ön (very formal) / maga (older formal), and Finnish te (formal) default to formal in business and consumer content. The model maps source register to target register where the distinction exists.
Yes — Turkish dotless i (ı/I) and dotted i (i/İ) are distinct letters and round-trip exactly. Unicode casing rules for Turkish (the i ↔ İ ↔ I ↔ ı locale) are applied where the target requires case changes.
Finnish and Hungarian both write compounds without spaces (Finnish "kirjastonjohtaja" = "library director"). The model splits the compound, translates each part, and emits the result as a multi-word phrase in non-agglutinative targets.
Hungarian uses Last-First name order (the European exception); the model preserves Last-First when emitting Hungarian and flips to First-Last for other European targets. Turkish and Finnish use First-Last.
Yes — Turkish ş, ç, ğ, ı/İ, ü, ö; Finnish ä, ö; Hungarian á, é, í, ó, ö, ő, ú, ü, ű; all round-trip cleanly and are emitted in the target output where the target uses them.
Modern loanwords (computer terms, brand names, internet vocabulary) stay close to the source spelling in Turkish (computer → bilgisayar but laptop → laptop). Hungarian and Finnish are more aggressive at coining native equivalents. The model emits the form standard in the target.
No — output uses standard Istanbul Turkish / Standard Finnish / Standard Hungarian. Dialect-marked source is normalized to the standard before translation.
Agglutinative languages pack more meaning per word than English, so a 5,000-character English source typically produces 4,000-4,500 characters of Turkish / Finnish / Hungarian. Up to 10,000 characters per web request, 50,000 per API.