Watch: Microsoft’s ‘Star Trek’ Universal Translator — Would It Have Downsides?

Microsoft may have co-opted Star Trek a full century early by demonstrating an honest-to-goodness universal translator.

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Microsoft may have co-opted Star Trek a full century early by demonstrating an honest-to-goodness universal translator — one that not only renders what you’re saying into another language in real time, but that manages to sound like you while doing so.

In fact, assuming everything really is as it appears in the video above, Microsoft just pulled off something pretty amazing — much more impactful, in theory anyway, than a mere voice recognition app like Apple’s Siri.

Microsoft’s global head of research, Rick Rashid, demonstrated the surprisingly mature technology to a crowd of 2,000 students and teachers on Oct. 25 at the 14th annual Computing in the 21st Century Conference, held in Tianjin, China (the fourth largest city in the country).

Standing onstage with a large screen above him, Rashid’s speech was at first rendered on the screen as English text, the words appearing as spoken with near-perfect accuracy. A “recognizability” percentile in the lower-right-hand corner indicated how identifiable Rashid’s speech patterns were, operating well above 70% for most of the presentation.

After walking through a few watershed moments in speech-recognition research, Rashid shifted to live speech translation, explaining that Microsoft’s approach to the process happens in three steps. First, the company converts spoken English word-by-word into Chinese text. Next, the words are rearranged, since the word order of a Chinese sentence is different from its English analogue. Last, the newly translated Chinese text is converted back into speech, and — here’s the really clever part — made to sound as if the original speaker were vocalizing in the translated language (you can hear this yourself, starting around the video’s 7:30 mark).

“In the realm of natural user interfaces, the single most important one — yet also one of the most difficult for computers — is that of human speech,” wrote Rashid in a followup blog post. “For the last 60 years, computer scientists have been working to build systems that can understand what a person says when they talk.”

In the course of its research, Microsoft says it’s been able to reduce errors by 30% — an increase, according to the company, from one word in four to five being incorrect, to just one word in seven to eight. Rashid calls that “the most dramatic change in accuracy since the introduction of hidden Markov modeling in 1979.” (Markov modeling is a math concept dealing with probability theory.)

And with its speech-language translation engine, Rashid argues:

…we may not have to wait until the 22nd century for a usable equivalent of Star Trek’s universal translator, and we can also hope that as barriers to understanding language are removed, barriers to understanding each other might also be removed. The cheers from the crowd of 2000 mostly Chinese students, and the commentary that’s grown on China’s social media forums ever since, suggests a growing community of budding computer scientists who feel the same way.

So that’s Microsoft pitch — impressive, real enough and clearly promising for the future of engagement between speakers of different languages.

But would a universal translator also have downsides?

I can think of one in the Nicholas Carr “Is Google Making Us Stupid?” vein — the notion that externalizing so much of what we do mentally with computers and via the Internet is making us shallower, cognitively speaking. And academic research into the Internet’s role as an extension of our brains suggests that the more we’re sure of having access to information in the future, the less we’re able to summon it from memory.

So what happens if we outsource our brains linguistically? Would a universal translator render language instruction obsolete? Why, if you could just clip something onto your shirt, Star Trek-style, would you bother to actually learn a second or third or fourth language, when a computer could just play wingman and save you the effort? Doesn’t learning another language actually increase our brainpower? Would externalizing that diminish us somehow?

You’ve probably heard how learning a second language can be a serious brain booster. In an interview on the subject, Therese Sullivan Caccavale, president of the National Network for Early Language Learning, references a 2007 Harwich, Massachusetts study, which she explains “showed that students who studied a foreign language in an articulated sequence outperformed their non-foreign language learning peers on the Massachusetts Comprehensive Assessment System (MCAS) test after two-three years and significantly outperformed them after seven-eight years on all MCAS subtests.”

She continues:

Furthermore, there is research … that shows that children who study a foreign language, even when this second language study takes time away from the study of mathematics, outperform (on standardized tests of mathematics) students who do not study a foreign language and have more mathematical instruction during the school day. Again, this research upholds the notion that learning a second language is an exercise in cognitive problem solving and that the effects of second language instruction are directly transferable to the area of mathematical skill development.

Of course futurists and brain augmentation wonks will argue that we’re fast approaching a point at which the distinction between brains and computers becomes irrelevant. But in the meantime, amazing as technology like this is — in particular its promise to let us speak any language (estimates put the number of “living languages” in the world at just under 7,000) – it raises interesting new questions about the role of cognitive externalization: the pros and cons of handing increasingly more of what we used to do with our biological “human tech” over to computers.

Microsoft may have co-opted Star Trek a full century early by demonstrating an honest-to-goodness universal translator — one that not only renders what you’re saying into another language in real time, but that manages to sound like you while doing so.

In fact, assuming everything really is as it appears in the video above, Microsoft just pulled off something pretty amazing — much more impactful, in theory anyway, than a mere voice recognition app like Apple’s Siri.

Microsoft’s global head of research, Rick Rashid, demonstrated the surprisingly mature technology to a crowd of 2,000 students and teachers on Oct. 25 at the 14th annual Computing in the 21st Century Conference, held in Tianjin, China (the fourth largest city in the country).

Standing onstage with a large screen above him, Rashid’s speech was at first rendered on the screen as English text, the words appearing as spoken with near-perfect accuracy. A “recognizability” percentile in the lower-right-hand corner indicated how identifiable Rashid’s speech patterns were, operating well above 70% for most of the presentation.

After walking through a few watershed moments in speech-recognition research, Rashid shifted to live speech translation, explaining that Microsoft’s approach to the process happens in three steps. First, the company converts spoken English word-by-word into Chinese text. Next, the words are rearranged, since the word order of a Chinese sentence is different from its English analogue. Last, the newly translated Chinese text is converted back into speech, and — here’s the really clever part — made to sound as if the original speaker were vocalizing in the translated language (you can hear this yourself, starting around the video’s 7:30 mark).

“In the realm of natural user interfaces, the single most important one — yet also one of the most difficult for computers — is that of human speech,” wrote Rashid in a followup blog post. “For the last 60 years, computer scientists have been working to build systems that can understand what a person says when they talk.”

In the course of its research, Microsoft says it’s been able to reduce errors by 30% — an increase, according to the company, from one word in four to five being incorrect, to just one word in seven to eight. Rashid calls that “the most dramatic change in accuracy since the introduction of hidden Markov modeling in 1979.” (Markov modeling is a math concept dealing with probability theory.)

And with its speech-language translation engine, Rashid argues:

…we may not have to wait until the 22nd century for a usable equivalent of Star Trek’s universal translator, and we can also hope that as barriers to understanding language are removed, barriers to understanding each other might also be removed. The cheers from the crowd of 2000 mostly Chinese students, and the commentary that’s grown on China’s social media forums ever since, suggests a growing community of budding computer scientists who feel the same way.

So that’s Microsoft pitch — impressive, real enough and clearly promising for the future of engagement between speakers of different languages.

But would a universal translator also have downsides?

I can think of one in the Nicholas Carr “Is Google Making Us Stupid?” vein — the notion that externalizing so much of what we do mentally with computers and via the Internet is making us shallower, cognitively speaking. And academic research into the Internet’s role as an extension of our brains suggests that the more we’re sure of having access to information in the future, the less we’re able to summon it from memory.

So what happens if we outsource our brains linguistically? Would a universal translator render language instruction obsolete? Why, if you could just clip something onto your shirt, Star Trek-style, would you bother to actually learn a second or third or fourth language, when a computer could just play wingman and save you the effort? Doesn’t learning another language actually increase our brainpower? Would externalizing that diminish us somehow?

You’ve probably heard how learning a second language can be a serious brain booster. In an interview on the subject, Therese Sullivan Caccavale, president of the National Network for Early Language Learning, references a 2007 Harwich, Massachusetts study, which she explains “showed that students who studied a foreign language in an articulated sequence outperformed their non-foreign language learning peers on the Massachusetts Comprehensive Assessment System (MCAS) test after two-three years and significantly outperformed them after seven-eight years on all MCAS subtests.”

She continues:

Furthermore, there is research … that shows that children who study a foreign language, even when this second language study takes time away from the study of mathematics, outperform (on standardized tests of mathematics) students who do not study a foreign language and have more mathematical instruction during the school day. Again, this research upholds the notion that learning a second language is an exercise in cognitive problem solving and that the effects of second language instruction are directly transferable to the area of mathematical skill development.

Of course futurists and brain augmentation wonks will argue that we’re fast approaching a point at which the distinction between brains and computers becomes irrelevant. But in the meantime, amazing as technology like this is — in particular its promise to let us speak any language (estimates put the number of “living languages” in the world at just under 7,000) – it raises interesting new questions about the role of cognitive externalization: the pros and cons of handing increasingly more of what we used to do with our biological “human tech” over to computers.