Google Translate reaching further

Somehow I missed it at the end of last year, but Google Translate has added nine new languages – four from the African continent, three from Asia, and Maori.

In Africa, we’re adding Somali, Zulu, and the 3 major languages of Nigeria.
  • Hausa (Harshen Hausa), spoken in Nigeria and neighboring countries with 35 million native speakers
  • Igbo (Asụsụ Igbo) spoken in Nigeria with 25 million native speakers
  • Yoruba (èdè Yorùbá) spoken in Nigeria and neighboring countries with 28 million native speakers
  • Somali (Af-Soomaali) spoken in Somalia and other countries around the Horn of Africa with 17 million native speakers
  • Zulu (isiZulu) spoken in South Africa and other south-western African countries with 10 million native speakers
Throughout Asia, we’re launching languages spoken in Mongolia and South Asia.
  • Mongolian (Монгол хэл), official language in Mongolia and also spoken in parts of China with 6 million native speakers
  • Nepali (नेपाली), spoken in Nepal and India with 17 million native speakers
  • Punjabi language (ਪੰਜਾਬੀ) (Gurmukhi script), spoken in India and Pakistan with 100 million native speakers
Thanks to the volunteer effort of passionate native speakers in New Zealand, we’re adding the language of the Maori people.
  • Maori (Te Reo Māori), spoken in New Zealand with 160 thousand speakers

Unbabel – Translation as a Service

How quickly things change. It’s been a while since I’ve had a chance to look at the state of translation and translation tech, and now it seems that all the latest trends have come together.

Unbabel combines the brash young entrepreneur, the youth in turn brings something akin to ignoratio elenchi – the byline is “Translation as a Service”

Human corrected machine translation service that enables businesses to communicate globally

dutifully adhering to the modern “X as a Service” line so necessary for venture capital funding without understanding the nature of translation (it’s always been a service), and as happens with this style of disruptive tech, poorly paid contractors making management rich.

Despite my reservations about the motivations of Unbabel’s direction and management, and my knowledge of what this will do to the translation industry, this is not unexpected. I’ve written before many times about the coming changes and the shake up the industry should by now be expecting. I would suggest that this is the final ramping up of this process, the next step will be a combination of the collapse of the industry. This will lead to two distinct results – a massive increase in the number of translated texts and a dramatic shrinkage of the employment prospects, but increase in the financial returns for those translators that stick at it long enough.

TechCrunch manages to say a lot

Unbabel’s secret sauce leverages artificial intelligence software and its stable of over 3,100 editors (or translators) to translate a website’s content from one language into its customer’s language of choice. First, its machine learning technology translates the text from source into the target language, at which point it uses its Mechanical Turk-style distribution system to assign editing tasks to the right translators, who then check the translation for errors and for stylistic inconsistencies.

Unbabel editors work remotely, via their laptops or mobile phones, on translations, which co-founder Vasco Pedro says provides the key to faster translations. This, combined with the efficiency of its task distribution and administration algorithms, provides a level of efficiency that allows editors to earn up to $10/hour working for Unbabel.

but without much analysis – the technology sector and it’s loyal heralds have never been good at analysis that didn’t revolve around profit and where it’s coming from

Human translation is really the gold standard as far as online translation goes, but for most companies, paying real, live humans to translate their content is an expensive proposition. In most cases, it’s either pony up the funds to pay for humans, or make due with machines (like publicly available tools akin to the unreliable Google Translate) and automated services. By combining both machine translation and human curation, the Unbabel founders not only believe they’ve created a novel solution to a persistent problem, but that they can offer a product that’s on par with pure human translation, faster, and at a fraction of the cost.

Note here the only mention is a “expensive proposition” and “fraction of the cost”. This was to be expected, and I lectured the translation industry that they should expect it. I did not expect the young turks to dismiss the expensive past without even an acknowledgement of the history, theory or purveyors of that industry. I guess that’s why they call them the blues.