This article is BS. Machine translation has been improving but it's still nowhere close to being able to provide real-time translation of spoken languages, and I bet anything it won't be there after another decade. I know for a fact that Baidu is throwing lots of money and people at fundamental R&D in translating Asian languages, and it's no piece of cake.<p>As for "earpieces whispering nearly simultaneous translations", it would be a cool party trick but I doubt they'll work in real life.<p>These moonshot projects have been around for decades, and they make for some cool entertainment at conferences and demos in very tightly controlled settings. As for the predictions that "the software in the cloud connected to the earpiece in your ear will re-create the voice of the speaker", the author should take up writing bad science fiction.
I'm currently living in a country where I don't speak the language. I can't believe how incredible translation tools are. Even though I don't understand when people speak to me, I can write and read emails, and accomplish things that would be incredibly more difficult without this ability (e.g. talking to my insurance agent). And when I say I can read and write emails, I mean it can do so in about 1.5x longer than a native one. I have developed very basic abilities in the language (in the 2 months I've been here), and so I constantly use translation tools and check in both directions -- translate to the language, modify it to make sense according to my understanding -- translate it back to English -- all within the space of a couple of minutes.<p>I still miss out on learning more idiomatic expressions, but I imagine those will come in time. In the meantime, I am able to get a surprising amount of business done, in ways that would have been impossible before.<p>Not to mention that continuously doing all this translation of my written communications is making me learn the spoken language much faster. Although, for that, nothing replaces actually speaking with people, of course! ;) But it's much easier to bootstrap actual conversation when you've been learning individual words by reading and writing.<p>Overall I would say that automatic translation tools have made it possible for my life to move in directions that where language would have been a serious roadblock in a previous era.
I suspect real-time machine translation is within reach if the speakers are trained to use a restricted subset of their native language. Moreover, I suspect that this approach could be both realistic and useful.<p>This restricted subset situation is <i>de facto</i> already the case; existing tools don't handle regional dialects and colloquialisms. I just tried "嘘じゃねいぞ" (uso ja nei zo!) in Google Translate and it came up with rubbish because it doesn't know that "nei" is a variant of "nai".<p>The kinds of restrictions I'm thinking of are deeper: avoidance of the full variety in sentence structure, and excessive complexity, like compounded of relative clauses. Not to mention language-dependent tricks like double meanings depending on puns, and generally all figures of speech that do not translate.<p>A restricted subset of your native language is something which you already understand, and learning to speak it is easier than a whole different language.<p>People doing business abroad would just study that for a few weeks as part of the workflow.<p>The dialect could become richer and thus less restricted as time goes on, making it easier to use. It could be customizable as well, to a particular speaker's idiosyncrasies. If a given speaker often uses some figure of speech out of habit, it could just be defined for that speaker, with a hand-crafted translation to various languages.
I've been learning Japanese as of late, and automated translation tools are near useless for anything but sentences that are just a few words stringed together (and even then, nonsense is often returned as soon as a tiny bit of slang or metaphorical language is used). I also have friends who speak languages that are not part of the top 10 most spoken in the world (eg Finnish, Hungarian, etc) and trying to translate their Facebook statuses returns complete garbage.<p>Between languages that are fairly close to one another (such as French and Spanish), sure - you can pipe text from one language to another in Google Translate and the results will be mostly understandable (although still very awkward). But anything else, and automated translation still has ways to go. Turns of phrases, idioms, general syntax etc. are fairly similar between languages that are closely related, so automated translation has an easy job there (with the caveat that it starts falling apart as soon as slang or more colloquial expressions are used). But step any further than that, and it's a lost cause.<p>The article also assumes that there's a 1:1 mapping between everything you can express in every language, and that it's just a matter of software finding the right mapping for whatever you're saying into the destination language. But any translator will tell you that this couldn't be further from the truth - there are many things I can say in English to my Californian friends that don't really work in a French conversation with my Parisian friends (let alone in Mandarin or Japanese). At best you'll be met with blank stares, and at worst you'll be breaking etiquette in major ways. Part of learning a new language is learning the space of what can be expressed and how in that language.<p>For these reasons, I don't really buy the whole "earpiece that automagically lets you speak with anyone in the world" anytime in the next few decades. Which is fine, because learning languages is fun :)<p>On the other hand, I'm currently in the Netherlands for a conference, and everyone speaks flawless English. I've had a similar experience in Germany, Sweden, and a bunch of other countries (but not in my country of origin, France, where being terrible at English seems to be a point of pride). So maybe taking a page from their book when it comes to education is a better idea than waiting for technology to let us be lazy.
I think people are overestimating the word "language barrier". People often forget that the language barrier is not a one-sided problem. Communication is a collaborative effort (unless we're just spying them). I bet that something like keyword spotting for commonly used 3000 words is already pretty feasible, and that would greatly reduce the language barrier. Perfect translation is neither possible nor necessary to induce mutual effort.<p>(By the way, I've seen so many US tourists in Europe who don't even try to speak a single word in their language. They don't seem to know that a simple "thank you" in their native tongue would greatly reduce the barrier and change their sentiment towards the US. In this sense, I believe that technology is more or less neutral to mutual understanding, because not knowing a language (or the idea that not knowing a language is acceptable) can have adverse effects.)<p>Edit: a few grammatical errors. Damn my Japaneseness!
Yet another journalist who doesn't understand how languages actually work.<p>Other languages aren't just "English with different words and syntax". A single word can have dozens of different meanings, the set of different meanings of a word needn't be the same across languages. And even if you know the context the meaning doesn't have to be unambiguous. A perfect translation would need to recognize plausible ambiguities and retain them across languages.<p>Language is not code. Language is an expression of thoughts in a form that builds upon vaguely defined tokens. It's amazing that human language communication works this well at all given how ambiguous and faulty it actually is in practice.
The problem is that we still haven't been able to write a system to accurately recognize the words that are being spoken. Differences in diction, dialects, and accents make it difficult to accomplish. Just look at what Microsoft, Google, and Apple are doing - as good as they are, they're nowhere close to where they need to be.<p>Even once we solve the voice capture issue, I suspect that we'd still run into many areas where the computer would have problems determining the proper context necessary to accurately translate the text. Whatever system is performing the translation would have to maintain a history of the conversation in order to have any hope of understanding context, and at a gathering where you could have multiple conversations occurring at the same time, the process gets even harder.<p>I think the only part of the author's belief that we're close to achieving is being able to have the computer use the original speaker's voice. Siri and Cortana could already sound more human, but people are currently more comfortable having them sound robotic. I'm sure that will change in time, however.
"...in ten years time." To quote XKCD's translation (sic!), "we haven't finished inventing it yet, but when we do, it'll be awesome." <a href="https://xkcd.com/678/" rel="nofollow">https://xkcd.com/678/</a><p>This is the same tired old story that keeps on making rounds for the sixth decade now - "machine translation kind of sucks now, but it will be solved within the next decade!!!!!!!!1!" This is still very much a current paper - note the publication date: <a href="http://www.mt-archive.info/Bar-Hillel-1951.pdf" rel="nofollow">http://www.mt-archive.info/Bar-Hillel-1951.pdf</a>
真有意思。I see a lot of dismissals of the projections in this article. Thirty years ago, just as I was working for several years as a Chinese-English interpreter, I would have agreed with all those dismissals. I no longer agree. As some of the subcomments here have pointed out, all that automated translation and interpretation have to do is become less expensive than either a) learning the relevant language yourself or b) hiring good-quality human translators and interpreters. Automated translation and interpretation is already well along that path.<p>A crucial skill for a professional interpreter or a casual language-learner is "lexicalization," figuring out what the correct match is between what is possibly a phrase in one language but only a single morpheme that is part of a larger word in another language. But the huge advantage automated translation solutions have is shared learning and long-lasting memory. If the lexicalization is built into a database, for example a database kept by Apple, Google, IBM, or some other multinational provider of translation services, that learned information can be deployed in products over and over and over again. In the end, that's all that it takes for automated translation and interpretation to do better at equal cost (or as well at less cost) compared to human language-learning or human language services. I got out of interpreting for a living years ago, because I finally came around to the understanding of how little I could compete with the worldwide efforts made with new technology to tackle language problems. I still think learning natural modern human languages is a very intellectually enriching activity, and all my children do that, but we expect to live in a world a decade from now with very good real-time interpreting and translation systems for a wide variety of language pairings.
The idea that one can translate words without understanding what is being said, seems rather similar to an idea that one can infer the meaning of words from their constituent letters.
Meaning not only works simultaneously on so many technically inaccessible levels (context, expectations, allusions, previous experiences, etc.), anything mildly interesting (not to mention proper literature), is based by definition on a <i>deviation</i> from established meanings.
Compare this line from the WSJ article:<p>> A decade from now, I would predict, everyone reading this article will be able to converse in dozens of foreign languages, eliminating the very concept of a language barrier.<p>with these excepts from The Guardian at <a href="http://www.theguardian.com/technology/2016/feb/10/texas-regional-accent-siri-apple-voice-recognition-technology" rel="nofollow">http://www.theguardian.com/technology/2016/feb/10/texas-regi...</a> (referenced two days ago on HN at <a href="https://news.ycombinator.com/item?id=11077168" rel="nofollow">https://news.ycombinator.com/item?id=11077168</a> ):<p>> Y'all have a Texas accent? Siri (and the world) might be slowly killing it<p>> Voice recognition tools such as Apple’s Siri still struggle to understand regional quirks and accents, and users are adapting the way they speak to compensate.<p>> ... “I’ve had a bunch of people from Australia and India say they only really get along with Siri if they fake an American accent,” said Lars Hinrichs, a sociolinguist at the University of Texas at Austin.
It must work offline. One of the reasons is that tourists often don't buy a data plan (imagine a tour of Europe with a different country every couple of days) and wifi is not where you might need machine translation most, on the road.
If I access this article via a google search, it is still paywalled. I see experts-exchange seems to be doing this again also. I thought this was against google's terms & conditions, no?
><i>You could host a dinner party with eight people at the table speaking eight different languages, and the voice in your ear will always be whispering the one language you want to hear.</i><p>And at this hypothetical dinner party, what would the earpieces whisper in English (or most other languages) when the Japanese guests said いただきます?<p>Some words just don't have a translation in other languages.<p><a href="https://www.google.com/search?q=いただきます&tbm=isch" rel="nofollow">https://www.google.com/search?q=いただきます&tbm=isch</a>
I live abroad and speak far from fluently in a foreign language. I'm personally invested in machine translation improving, and I really hope it does.<p>> Today’s translation tools were developed by computing more than a billion translations a day for over 200 million people. With the exponential growth in data, that number of translations will soon be made in an afternoon, then in an hour. The machines will grow exponentially more accurate and be able to parse the smallest detail. Whenever the machine translations get it wrong, users can flag the error—and that data, too, will be incorporated into future attempts.<p>If this is the reasoning that we will be there in 10 years, it is ridiculously optimistic. I'm pretty sure that there is a exponential fall off from common phrases to a long tail of more nuanced, not as often uttered language. A million people punching in "where is the bathroom?" is not going to make the machine know how to impart the acerbic wit of a phrase from a Palahniuk book to a Japanese business man. Good luck finding someone skilled enough in both languages and cultures to be able to correct the error.<p>Real skills in multiple languages requires an intellect to parse the situations. While I personally hope that will one day be achievable with AI, I have to think that we are still a long way off.
The benefits to this kind of thing are being able to be very specific and go deeper into the subject matter with one's second or third languages. Plus I might argue that smaller languages won't need to die (if everyone can get along and do business in their own tongue). The drawback is that perhaps people who learn languages in the near future will seem like those who study Latin ever since it became a "dead" language.
I speak Arabic, French, English and Spanish; the last 3 are "easier" to translate interchangeably. Good luck breaking the Arabic barrier, each Arab nation has its own dialect and no one hardly speaks "traditional" Arabic anymore. The language itself is very rich and dense, even machine text translation has a long way to go, let alone real-time voice translation. This article is fiction at best.
I thought this was about how the entire world is getting to a point where they are able to speak and understand basic English.<p>There are certainly countries and population groups that do not speak English well, but it has changed significantly the last 10 years.<p>I wonder if we will get there before 100% accurate automatic translation.
For an example of the state of automatic translation c.2010 I give you this:<p>This is question, engish is faulty therefore the right excused is requested. Thank google to translate to help. SORRY!!!!!<p>At often, the goat-time install a error is vomit. To how many times like the wind, a pole, and the dragon? Install 2,3 repeat, spank, vomit blows<p>14:14:01.869 - INFO
[edu.internet2.middleware.shibboleth.common.config.profile.JSPErrorHandlerBeanDefinitionParser:45]
- Parsing configuration for JSP error handler.<p>Not precise the vomit but with aspect similar, is vomited concealed in fold of goat-time lumber? goat-time see like the wind, pole, and dragon? This insult to father's stones? JSP error handler with wind, pole, dragon with intercourse to goat-time? Or chance lack of skill with a goat-time?<p>Please apologize for your stupidity. There are a many thank you<p>(from <a href="https://lists.internet2.edu/sympa/arc/shibboleth-users/2010-09/msg00304.html" rel="nofollow">https://lists.internet2.edu/sympa/arc/shibboleth-users/2010-...</a> )