Languages and locales supported by Amazon Lex V2 - Amazon Lex

Languages and locales supported by Amazon Lex V2

Amazon Lex V2 supports a variety of languages and locales. The languages that are supported, the features that support these languages, and language-specific guidance to improve your bot's performance are provided in this topic.

Supported languages and locales

Amazon Lex V2 supports the following languages and locales.

Code Language and locale
ar_AE Gulf Arabic (United Arab Emirates)
ca_ES Catalan (Spain)
de_AT German (Austria)
de_DE German (Germany)
en_AU English (Australia)
en_GB English (UK)
en_IN English (India)
en_US English (US)
en_ZA English (South Africa)
es_419 Spanish (Latin America)
es_ES Spanish (Spain)
es_US Spanish (US)
fi_FI Finnish (Finland)
fr_CA French (Canada)
fr_FR French (France)
hi_IN Hindi (India)
it_IT Italian (Italy)
ja_JP Japanese (Japan)
ko_KR Korean (Korea)
nl_NL Dutch (The Netherlands)
no_NO Norwegian (Norway)
pl_PL Polish (Poland)
pt_BR Portuguese (Brazil)
pt_PT Portuguese (Portugal)
sv_SE Swedish (Sweden)
zh_CN Mandarin (PRC)
zh_HK Cantonese (Hong Kong)

Languages and locales supported by Amazon Lex V2 features

The following table lists Amazon Lex V2 features that are limited to certain languages and locales. All other Amazon Lex V2 features are supported in all languages and locales.

Feature Supported languages and locales
AMAZON.AlphaNumeric All languages and locales except Korean (ko_KR)
AMAZON.KendraSearchIntent English (US) (en_US)
Creating a custom vocabulary to improve speech recognition

English (UK) (en_GB)

English (US) (en_US)

Automated Chatbot Designer English (US) (en_US)
Region availability

The following languages and locales are not available in the Asia Pacific (Singapore) (ap-southeast-1) and Africa (Cape Town) (ap-south-1) Regions:

  • Gulf Arabic (United Arab Emirates) (ar_AE)

  • Catalan (Spain) (ca_ES)

  • Finnish (Finland) (fi_FI)

  • Hindi (India) (hi_IN)

  • Dutch (The Netherlands) (nl_NL)

  • Norwegian (Norway) (no_NO)

  • Polish (pl_PL)

  • Portuguese (Brazil) (pt_BR)

  • Portuguese (Portugal) (pt_PT)

  • Swedish (sv_SE)

  • Mandarin (PRC) (zh_CN)

  • Cantonese (Hong Kong) (zh_HK)

Setting intent context English (US) (en_US)
Using a custom grammar slot type

English (Australia) (en_AU)

English (UK) (en_GB)

English (US) (en_US)

Using multiple values in a slot English (US) (en_US)
Using runtime hints to improve recognition of slot values

English (UK) (en_GB)

English (US) (en_US)

Using spelling styles to capture slot values

English (Australia) (en_AU)

English (UK) (en_GB)

English (US) (en_US)

Using voice transcription confidence scores

English (UK) (en_GB)

English (US) (en_US)

Language guidance for Amazon Lex V2

To improve your bot's performance, you should adhere to these guidelines for the following languages.

Arabic

The variety of Arabic that Amazon Lex V2 is trained on is Gulf Arabic. Keep this in mind when providing sample utterances for your bot. Note that Arabic script is written from right to left.

Hindi

Amazon Lex V2 is able to serve Hindi end-users who switch freely between Hindi and English. If you plan to build a bot that supports this language switching, we recommend the following best practices:

  • In the bot definition, write English words in Latin script.

  • At least 50% of your sample utterances should represent language switching within the same sentence. In these utterances, use Devanagari script for Hindi words and Latin script for English words (for example, "मैं ticket book करना चाहता हूं।").

  • If you expect users to communicate with the bot using Hindi words in Latin script or English words in Devanagari script, then you should include examples of Hindi words in Latin script (for example, "mujhe ek ticket book karni hai") and English words in Devanagari script (for example, "मुझे टिकट की बुकिंग में मदद चाहिए") in your sample utterances.

  • If you expect users to communicate with the bot using sentences that are completely in Hindi or completely in English, then you should include sample utterances that are fully in one language (for example, "I want to book a ticket").