All posts in “Language”

Learn Spanish with this innovative podcast

If you’ve ever tried to learn a language, you’ll know how important listening can be. 

That’s why Duolingo has launched the Duolingo Spanish Podcast, for English speakers who are learning Spanish. The first episode is available for free on Duolingo’s website, iTunes, Google Play Music, Spotify, and Stitcher. New episodes will roll out every Thursday. 

Each 15-minute episode is a narrative nonfiction story, similar to an episode of This American Life. Though they take place all around the world, the episodes feature Latinx characters, and discuss Latinx culture. 

The podcast is hosted by Martina Castro, co-founder of NPR’s Spanish language podcast Radio Ambulante. She is also the founder and CEO of Adonde Media, a bilingual podcast production company. 

Castro narrates the stories slowly in clear, intermediate-level Spanish. A paragraph is read in Spanish first, followed by an English translation, with segments clocking in at about a minute long. 

The English translations make it easy to check how much of the preceding segment you understood. They can also pull you back into the story if you got lost, or zoned out, during the Spanish section. 

Don’t expect the monotonous listening exercises from your high school Spanish class (or those you might hear on the Duolingo app itself). The stories are interesting, unnerving, heartwarming, and a unique portrait of Latinx culture.

Having taken four years of high school Spanish many years ago, I was able to get the gist of each section if I focused hard (though the English translations were certainly helpful). That said, you’ll want to listen at a time when you can focus — my intermediate-speaker’s brain had a lot of trouble translating if it was also doing something else. 

The first episode features the story of Rodrigo Soberanes, a Mexican journalist, who builds a friendship with a disgraced soccer player and makes a documentary about it. 

Upcoming segments will document a Chilean journalist who unexpectedly meets her future (Chilean) husband on a trip to China, and a woman’s journey to build a life in Buenos Aires after her boyfriend (whom she moved there for) leaves her.  

Duolingo told Mashable that it hopes the podcast will motivate intermediate and advanced Spanish learners to keep up with their studies throughout their daily, while communing, exercising, etc. (But as I said, for speakers as inexperienced as me, this is probably wistful thinking). 

It also hopes users who have completed Duolingo’s Spanish course will maintain their grasp on the language (and, incidentally, their involvement with Duolingo) by listening to the podcast regularly. 

The company also noted that Spanish speakers who are learning English could benefit from the podcast. 

If you want to learn Spanish, and you love a good story, check this podcast out. 68d8 b4a2%2fthumb%2f00001

Flitto’s language data helps machine translation systems get more accurate

Simon Lee, founder and CEO of Flitto

Artificial intelligence-powered translation is becoming an increasingly crowded category, with Google, Microsoft, Amazon and Facebook all working on their own services. But tech still isn’t a match for professional human translations and machine-generated results are often hit-and-miss. One online translation service, Flitto, is now focused on providing other companies with the language data they need to train their machine translation programs.

Headquartered in Seoul, Flitto launched in 2012 as a translation crowdsourcing platform. It still provides translation services, ranging from a mobile app to professional translators, for about 7.5 million users. About 80% of its revenue, however, now comes from the sale of language data, called “corpus,” to customers such as Baidu, Microsoft, Tencent, NTT DoCoMo and the South Korean government’s Electronics and Telecommunications Research Institute.

When Flitto launched five years ago, its main competition was Google Translate, says founder and chief executive officer Simon Lee. Google Translate delivered mixed results, but professional translation services were inaccessible for most people. Flitto, whose backers include Japanese game developer Colopl, was created to combine the two. It works with 1.2 million human translators who are paid if their translation is picked by the requestor.

Then in 2016, Google introduced its neural machine translation system, which improved the accuracy of Google Translate. Now many big tech companies, including Microsoft, Amazon, Facebook and Apple, are focused on developing their own artificial intelligence translation tools.

Even though results are getting better, they are still imperfect. AI-based translation systems need a ton of data to train, which is where Flitto comes in.

“There are different ways to translate something that gives different meanings in different situations, so there needs to be a huge set of data and a human checking all of that data to see if it is right or wrong,” says Lee.

He adds “it’s difficult to build up a corpus and IT companies don’t like building corpus because they focus on technology.”

Flitto’s app provides a machine translation first, then crowdsourced translations if requested.

Flitto’s corpus includes sets of human-translated sentences from its crowdsourcing service, which is used for things like slang, pop culture references or dialects that might stymie a machine translation service. Over the last five years, Lee says Flitto has accumulated more than 100 million sets of translated language data.

Corpus providers include the Oxford University Press, which gives researchers access to the Oxford English Corpus, and companies like Microsoft and Google that built corpus to train their systems. But there is still constant demand for new corpus because they take a lot of resources to create. While programs like Deepmind’s AlphaGo were able to train themselves with almost no human help, machine translation still needs a human touch.

“In other fields, machines can create their own data, but in language and translation it’s impossible for machines to create translation data by themselves,” says Lee. “So there always have to be human translators who go through all that data.”

Blue Canoe takes on language learning with a focus on pronunciation

If you want to pick up a new language, there’s no shortage of options, and free ones, at that. But one aspect of the process that has been neglected is pronunciation, which is an especially important part of it for professionals. Online, learning pronunciation is generally “hear a recording, then repeat it (to an empty room).” A new platform, Blue Canoe Learning, uses an established curriculum and machine learning to make things easier and more effective. It’s the first company to join AI2’s new incubator in Seattle, and has raised a $1.4 million round to expand its operations.

There are millions of English learners out there, many of whom speak it as their first language, but still find themselves unable to make themselves understood especially to Americans, who are particularly underexposed to certain accents.

The reality is that American English is the international language of many industries, and anyone in one of them, whether they’re call center employees, software engineers or executives, can benefit from being able to adopt an American-like accent. Their employers know that too, so Blue Canoe is going straight to them instead of adopting a direct-to-consumer approach.

I say potato…

The trouble with teaching pronunciation is that it’s not just about telling people how to say something correctly, but hearing how they say it and providing corrective guidance. That kind of personal feedback is hard to scale.

It’s especially difficult when you consider the neurological limitations of adult language learners. Unless you learn certain sounds at a young age, your brain eventually discards the mechanism for hearing them, making it difficult for some speakers to even understand that they’re pronouncing something incorrectly. (I had this experience in China recently when I tried to get directions to Futian; I got it right on the eighth or ninth try.)

Add to this that in American English, you have five vowels but 14 vowel sounds, and it’s a recipe for confusion.

“People haven’t focused on the last mile,” Blue Canoe founder Sarah Daniels told me. “They say they do spoken learning, but it’s glorified listen and repeat.”

One attempt to address this, offline anyway, has been the Color Vowel System, which relies on mnemonics and rhythm to help unlock sounds in your brain that you may not even know are there. Each vowel sound is associated with a color and alliterative phrase: green tea or brown cow, for instance. So to learn to say “speed,” learners would be instructed to say “green tea speed.” The repetition and color association, theoretically, help with retention and aid in producing the vowel sounds in question.

I say theoretically not because I personally doubt it, but because there isn’t a lot of literature on this; pronunciation is a tricky thing to measure compared with vocabulary or written proficiency — very subjective. But the Peace Corps, State Department and several major universities have adopted the system, so until the studies come out I’m okay with trusting their judgment.

Scaling the system

Blue Canoe (itself a mnemonic phrase) has worked to digitize the Color Vowel System and package it as an app. It’s still at a very early stage, with more content planned as the company learns from its pilot programs.

Users play a card game (the first of several games and activities to be included) that requires them to say the vocabulary word on the card they play; a machine learning system listens and identifies whether they have pronounced it correctly, and if not, gives relevant feedback.

At first I thought the system would have been trained on reams of American English speaker data, and analyze the delta between the waveforms, but it’s smarter than that. Instead, Blue Canoe had people with various accents speaking, and their pronunciation was annotated word by word by professionals. So an “r” pronounced with a roll (by, for example, a French speaker) would be treated differently than an “r” pronounced closer to “l” (by a Japanese speaker). Stressing a different syllable from Americans (the most common difference) will also be detected.

The number and type of errors also lets the app create an overall rating, and highlight words or sounds the speaker is improving on, needs help with and so on. Part of the plan is to track these ratings and compare them to professional, in-person ratings in order to validate them as an automated, objective score of a user’s pronunciation progress. That alone would be a useful tool for companies, but the ability to improve that score, of course, is likewise attractive.

Blue Canoe is already working with several companies to create special curricula with vocabulary and goals (and perhaps activities) tailored to their needs — technical terms, practice phrases, etc. This pilot program should last the next few months, and then second quarter next year should see a more public rollout, perhaps alongside documentation of the evaluation process and effectiveness of the app.

Kernel Labs led the $1.4 million round, but Blue Canoe will be getting its next few months of guidance and nurturing from the Allen Institute for AI, which earlier this year established a new, low-profile incubator program. This is their first selection for a company to adopt and invest in, though not necessarily representative of the type they’re going for: I had envisioned, when I talked with AI2 earlier, some kind of wild-haired geniuses who needed reining in by established AI brains. But this works too.

Featured Image: Bryce Durbin/TechCrunch

English teaching service VIPKID raises $200M and reportedly hits a $1.5B valuation

VIPKID, an online English teaching tool, announced today that it has raised $200 million in financing. That financing round values the company at $1.5 billion, according to a report by Bloomberg.

That wouldn’t just give VIPKID unicorn status — it also exposes a huge amount of demand there is in China and other countries as a tool to learn English from English speakers. VIPKID had raised $100 million in financing in August last year and already seemed to have quite a bit of momentum at the time. This financing round was led by Sequoia Capital, including a strategic investment from Tencent.

VIPKID is a play that taps into the growing need for training in English in China. While that’s the sweet spot for VIPKID right now, a service like this has natural applications in other countries as well. But at the moment, China is such a big market that it can already support a company with a $1.5 billion valuation that started in 2013. It’s become one of the largest resources of English tutoring for children and has attracted venture interest from basically all directions.

If you haven’t heard of VIPKID out in our little Silicon Valley bubble, it’s probably for the reason above: it’s huge outside of the U.S. The company said that it has more than 20,000 teachers delivering lessons to 200,000 paying students from 32 countries. It also said it had monthly revenue of $60 million in July this year and is projecting annual revenue of $750 million. Including this round, VIPKID has raised $350 million in venture financing.

VIPKID fills an interesting niche that helps English speakers — whether teachers or other professions — put in a bit of time to make a little extra money on the side. It’s a unique twist on the education model, putting it closer to an Uber model. There are other spins on online foreign language education like Duolingo, which raised $25 million at a $750 million valuation in July this year, but it seems like VIPKID has tapped into some kind of use case at the right time to get the attention of investors.

VIPKID founder Cindy Mi’s longtime focus on teaching English basically morphed into a platform that’s tapped into growing demand amid an increasingly global economic environment. We’ve reached out to VIPKID for some additional details about the funding round as well as the valuation and will update the post when we hear back.

Cindy Mi will also join us at TechCrunch Disrupt SF in September this yearWe’re incredibly excited to be joined by so many top names, and hope you’ll be there as well. Tickets are available for what’s shaping up to be another blockbuster Disrupt.

This gadget can let you talk in up to 80 languages

This pocket-sized gadget can translate up to 80 languages.
This pocket-sized gadget can translate up to 80 languages.

Image: Travis the translator

If you don’t have the time to learn a new language, you can typically depend on apps to help bridge a communication gap. For next level intra-language conversations in real-time, though, you might need some extra translation power.  

Travis, a remote control-like gadget that’s small enough to fit in your pocket, might be able to talk to almost anyone you encounter on your travels using AI. Its goal is to be able to communicate face-to-face with anyone at the touch of a button, since the device can auto-recognize speech to kick-start a conversation.

Travis’ makers claim it can translate 80 languages in real time when it’s online, ranging from Afrikaans to Welsh. The device can also access 20 more commonly spoken languages in offline mode, so travel in areas without clear network connection is less of a hassle. 

The Travis device has a touchscreen display for navigation, a quad core processor, built-in Bluetooth and Wi-Fi capabilities, and a slot for a SIM card. Its makers claim the battery can last for up to a week on standby mode — but online and offline use will drain it in six and 12 hours, respectively.  

There aren’t many details available about how Travis’ AI system works, which is slightly concerning. Its makers say the system was built by integrating the “best apps for each language” into the gadget, which selects the most suitable app for each conversation.  

The only footage of the device in action doesn’t show the final product, either. The demonstration, seen below, features a big, bulky prototype version of the system, so there’s clearly still quite a bit of work to be done before Travis is out in the world. 

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This isn’t the first real-time translation gadget on the market — there are others that we’ve actually seen in action IRL — but if it can fulfill its potential, the device could be a valuable tool for travelers and international businesspeople alike. 

Travis blew past its initial funding goal on IndieGoGo, where you can preorder your own device for $139 (at launch, it’ll run you $199). The translator is estimated to ship to backers later this year in July. 

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