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Spoken languages supported by Rekorder EN

The full list of languages Rekorder's speech-recognition engine can turn into captions, transcripts, summaries and chapters.

Rekorder doesn't care what language you speak while recording - the recorder itself works the same in any language. This list only matters afterward, for captions, transcripts, summaries and chapters, which Rekorder builds with a speech-recognition engine that only understands a specific set of languages.

Supported languages

Rekorder's speech-recognition engine can transcribe recordings in the following languages:

Language Language
Afrikaans Luxembourgish
Albanian Macedonian
Amharic Malagasy
Arabic Malay
Armenian Malayalam
Assamese Maltese
Azerbaijani Maori
Bashkir Marathi
Basque Mongolian
Belarusian Burmese (Myanmar)
Bengali Nepali
Bosnian Norwegian
Breton Norwegian Nynorsk
Bulgarian Occitan
Catalan Pashto
Chinese Persian
Croatian Polish
Czech Portuguese
Danish Punjabi
Dutch Romanian
English Russian
Estonian Sanskrit
Faroese Serbian
Finnish Shona
French Sindhi
Galician Sinhala
Georgian Slovak
German Slovenian
Greek Somali
Gujarati Spanish
Haitian Creole Sundanese
Hausa Swahili
Hawaiian Swedish
Hebrew Tagalog
Hindi Tajik
Hungarian Tamil
Icelandic Tatar
Indonesian Telugu
Italian Thai
Japanese Tibetan
Javanese Turkish
Kannada Turkmen
Kazakh Ukrainian
Khmer Urdu
Korean Uzbek
Lao Vietnamese
Latin Welsh
Latvian Yiddish
Lingala Yoruba
Lithuanian

How this affects you

  • Recording itself is unaffected. Speak any language you like on camera or in the audio track. The list above only matters once you generate captions afterward.
  • One language per recording. Rekorder expects a single dominant spoken language per recording. For picking the right one, or fixing a wrong auto-detected guess, see Caption languages, and how the language is chosen.
  • Same list on every plan. Free and Pro workspaces have access to the same languages.
  • Not available in Offline mode. Offline recordings can't be captioned at all, regardless of language. See What you give up in Offline mode.
  • Recognition quality varies. Widely-spoken languages with more available training data, such as English, Spanish or French, tend to transcribe more accurately than less common ones.
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