Google Translate adds 24 languages and dialects, including Sanskrit and Bhojpuri

Edited By: Tanisha Rajput
Washington, United States Updated: May 12, 2022, 02:57 PM(IST)

According to the company, more than 300 million people speak these languages as their first or second language. Photograph:( Reuters )

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All of the languages added in the update will only be supported in the text translation feature, but the business plans to add voice to text, camera mode, and other capabilities in the near future.

Google has added 24 more languages to its Google Translate language translation tool. Translate currently covers a total of 133 languages used around the world. 

New Indian languages being introduced include Assamese, Bhojpuri, Sanskrit, Dogri, Konkani, Meiteilon (Manipuri), Mizo, and Maithili.

Google is also adding Quechua (Peru, Bolivia, Ecuador), Guarani (Paraguay and Bolivia, Brazil and Argentina), and Aymara (Bolivia, Peru, and Chile) to the service for the first time, as well as an English-based Dialect Krio (Sierra Leone).

On May 11, Google Translate users will start getting these new languages, with all users having access by the end of the week.

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The list of languages also includes Ewe (Ghana and Tongo), Kurdish (Iraq), Sepedi (South Africa), Twi (Ghana), Oromo (Ethiopia and Kenya), Tsonga (Eswatini, South Africa, Zimbabwe and Mozambique).

According to the company, more than 300 million people speak these languages as their first or second language. It further added that these languages are also the first ones added by Google utilising a translation known as Zero-Shot Machine translation, a learning model that translates any test into another language by just viewing the texts. 

Full list of 24 new languages added to Google Translate

Assamese (used by about 25 million people in Northeast India)

Aymara (used by about two million people in Bolivia, Chile and Peru)

Bambara (used by about 14 million people in Mali)

Bhojpuri (used by about 50 million people in northern India, Nepal and Fiji)

Dhivehi (used by about 300,000 people in the Maldives)

Dogri (used by about three million people in northern India)

Ewe (used by about seven million people in Ghana and Togo)

Guarani (used by about seven million people in Paraguay and Bolivia, Argentina and Brazil)

Ilocano (used by about 10 million people in northern Philippines)

Konkani (used by about two million people in Central India)

Krio (used by about four million people in Sierra Leone)

Kurdish (Sorani) (used by about eight million people, mostly in Iraq)

Lingala, used by about 45 million people in the Democratic Republic of the Congo, Republic of the Congo, Central African Republic, Angola and the Republic of South Sudan

Luganda (used by about 20 million people in Uganda and Rwanda)

Maithili (used by about 34 million people in northern India)

Meiteilon (Manipuri) (used by about two million people in Northeast India)

Mizo (used by about 830,000 people in Northeast India)

Oromo (used by about 37 million people in Ethiopia and Kenya)

Quechua (used by about 10 million people in Peru, Bolivia, Ecuador and surrounding countries)

Sanskrit (used by about 20,000 people in India)

Sepedi (used by about 14 million people in South Africa)

Tigrinya (used by about eight million people in Eritrea and Ethiopia)

Tsonga (used by about seven million people in Eswatini, Mozambique, South Africa and Zimbabwe)

Twi (used by about 11 million people in Ghana)

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Sundar Pichai, the CEO of Alphabet, in his speech said, “"There is a long tail of languages that are underrepresented on the web today and translating them is a hard technical problem since translation models are usually trained with bilingual text. However, there is not enough publicly available bilingual text for every language.” 

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Because this is a new technology, Google chose to focus on languages with significant speaker populations and locations where technology is typically reserved, which led to work on a number of languages in Africa and India due to the presence of vast linguistic and ethnic groupings.

In a blog post, the business stated that while the technology isn't perfect now, they will continue to work on models to give the similar experience with existing languages.

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(With inputs from agencies)
 

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