51–60 of 124 posts
Fun thing to do: you can turn on transcribe audio on Youtube and directly compare how Google's speech recognition tech stacks up against Microsoft's.
Earlier quoted context omitted.
I don't follow your logic... Without those different languages, you wouldn't have anything to translate in the first place. If anything, this type of technology promotes independent and different languages, as it makes it so much easier to communicate with others regardless of your native tongue. Also, bravo to Microsoft; I'll remove my jaw from the floor after I watch your video a second time.
different languages emerged because of physical separation. As barriers have been reduced because of technology (both physical and communication barriers) there really aren't "borders" anymore. I can call someone in China right now if I wanted to, something impossible to do even just 100 years ago. So if we can all talk to each other across the world in real time, and we can all understand each other because of this…
To someone who spent years learning Chinese as a second language, and then made my living for years as a Chinese-English interpreter, that was pretty impressive. The economics of the issue is that a machine interpreter just has to be as good as a human interpreter at the same cost. That's a reachable target with today's computer technology. EVERY time I've heard someone else interpreting English or Chinese into the o…
Human translators are so expensive today that they are only used in situations where the translation has to be correct -- diplomacy, courtrooms, books, etc. Until a machine is much better than a human, these use cases won't switch to machine translation (similarly, self-driving cars won't be allowed until they are proven to be much safer than human drivers).
On the other hand, there's a large casual market for machine translations today for situations like reading foreign Web sites, chatting with people in different countries, reading Tweets in a different language, etc.
My current client is specialising in speech recognition, speech synthesis and automatic translation. They have something similar, focused on enterprise customers. I find this subject very interesting. I am a Ruby guy and I only marginally get in contact with their C++ code, but from what I learned so far this stuff is extremely memory and CPU hungry. It also depends on having been fed the right amounts of input. That…
> and in many cases the content can be obtained in different languages I wonder if there's some feedback loop caused by websites that used google translate itself to offer the alternative versions :)
I was just pondering today why PCs have adopted spell checking as a standard feature but don't appear to use context techniques for word checking or grammar checking yet. Perhaps I'm just using the wrong apps? The speaker says "to take in much more data" but it gets parsed by the speech-to-text as "to take it much more data" which is such an unlikely phrase I can't really work out why it's not auto-corrected. The phr…
- Because grammar is typically more expressive, and dependent upon a concept that otherwise may not exist in words. Thus statistical grammar models and context checkers would be much more volatile to generating nonsense from user input (along the lines of the Sokal hoax) or restricting output to a range of acceptable models (giving the machine its own voice in a sense). That leads to the second thing...
- It kills freedom and creativity (or at least, how we receive it). Imagine comedy routines in stoic deadpan. Perfunctory exchanges in formal constructions (and vice versa). Obviously you can avoid all of these situations if you wanted to, but in that case it should probably be saved for those special occasions. It could probably help a lot of businessmen wanting to write their statements and messages in shorthand without spewing boilerplate text. But it's potentially damaging to every child or student who is still finding out how they want to express themselves in the given context.
Note: I think it is fair to assume that grammar checking would include the ability to reformulate or generate text that obeys the relevant models. Spell checkers suggest spellings, grammar checkers have to suggest fixes and changes as well, and if we want to get any further than Win98 era Word it will probably have to have a plain old fix-it generator as well.
The implications of this kind of technology reaching consumers in the next decade or so are really interesting. If we can get to the point of having handheld devices that can accomplish live translation of spoken word, what exactly is the point of different languages anymore?
To someone who spent years learning Chinese as a second language, and then made my living for years as a Chinese-English interpreter, that was pretty impressive. The economics of the issue is that a machine interpreter just has to be as good as a human interpreter at the same cost. That's a reachable target with today's computer technology. EVERY time I've heard someone else interpreting English or Chinese into the o…
I don't think there will be much of an impact on the interpreter industry until the machine translations are significantly better than human translations. Human translators are so expensive today that they are only used in situations where the translation has to be correct -- diplomacy, courtrooms, books, etc. Until a machine is much better than a human, these use cases won't switch to machine translation (similarly,…
After watching this video, I'm fairly confident that a large part of the interpreting that I did could already be handled by this technology.