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IBM Strives For 'Superhuman' Speech Tech
robyn217 writes "IBM unveiled new speech recognition technology today that can comprehend the nuances of spoken English, translate it on the fly, and even create on-the-fly subtitles for foreign-language television programs. One of the projects perpetually monitors Arabic television stations, dynamically transcribing and translating any words spoken into English subtitles. Videos can then be viewed via a web browser, with all transcriptions indexed and searchable."
Which witch blew the blue candle out ?
Fry: heh, Yakov Smirnoff said it
Leela: No he didn't.
From The article "For now, all video processed through Tales is delayed by about four minutes, with an accuracy rate of between 60 and 70 percent" and "The accuracy rate could be increased to 80 percent, Roukos added"
Still even at 80 percent how good is this translation. If that 20% is the important parts of speech You could still be left clueless. Even the best Machine translations of text I have seen always leaves the text a bit garbled and confusticated.
I don't know how much delay is implied in the phrase "on the fly" , but I personally don' think there could ever be real time translation for the following reason. Sentences in different languages have different sentence structures. While in English the verb is usually the second part, in other languages the verb comes many times last (German). For the translator to get the second word of a sentence, it would have to wait till the end, of what could be a long sentence. This necessarily adds delay.
quis custodiet ipsos custodes
however the researchers stated "We still can't figure out what Bob Dylan is saying"
GB on TV: "We have prevailed"
Subtitle: "All your base are belongs to us"
Disclosure: I'm stupid
I cannot wait when I buty the first eBabelfish gadget that I will put in my ear so I can understand spoken language of my russian colegues... ;-) :-) I hope that someobody will not consider it as "important technology for the national security" and will not restrict it by any mean...
(I'm sure that this eBabelfish is already installed - not in my ear - but on the telecommunication centers...)
Well, I've got to get back to work. When I stop rowing, the slave ship just goes in circles.
I'm afraid this type of technology will be used as an exuse for people not to learn foreign languages, which is a shame.
It's not until you learn another foreign language that you realise how complex languages are, and how subtle. Learning another language can literally change the way you think about things.
This type of technology will make people think they completely understand a foreign language, but they won't. Their understanding will be crude, without the subtleties and cultural understanding.
I can speak English and Spanish fluently, and if I watch an English film with Spanish subtitles I'm always thinking - damn, they missed a good joke there, they got that wrong, etc. (Equally so with a Spanish film with English subtitles). And film subtitles are done by professional translators. God only knows what a terrible job a computer would make of film translation.
Hmm, instantaniously translation from arabic, wonder who "cough cough echelon cough!" they are marketing this to.. ?
More opportunities for Arabic speaking people to misinterpret western media.
I think you've got it the wrong way round haven't you? Did you mean to say "More opportunities for English speaking people to misinterpret Arabic media."?
...they should send it to Glasgow on a saturday night just after the pubs
have closed.
"Ye loooiii ahhh me jimmeh??! *belch* C'mere ya wee electrahnich bastid, I'll
shoo ye!"
May be IBM is going to make speech recognition true, but Bill Gates said that this was posible a long time ago. Simply genius.
-= If you fight Dragons long enough, you will become a Dragon =-
They really do it on the fly? You mean, [on the surface of] [a particular] [insect of a Musca domestica species]?
I have read a lot of auto-translated documents and it is always a good laughter in terms of "crapslation cabaret". So far, there is no technology that could auto-translate a text document succesfully. The "80% success" is a myth - they just count how many words were found in the vocabulary, not how many of them were put into a good context. A "fly" translated as an insect would be accounted as a success!
Even if you are not a bot but a human being with some knowledge of the other language and culture, it's very easy to involuntary offend someone or just to make a ridiculous faux-pas. Polish and Czech languages, for example, are very much alike and use common roots for many words, but because of the way both languages evolved, some neutral terms on one side of the border have become offensive on the other side. Czechs evolved an euphemism for sexual intercourse based on the verb "to look for". Poles still use this word when they look for something, which leads to constant crapslation cabaret gags when a Polish tourist appears in a Czech town "looking for a parking lot". Now, auto-translate this...
IBM has been one of the pioneers in speech recognition for a long time. However, indications are that Google (in the lab) has been making tremendous progress in translation. While the two companies are bound to be fierce competitors, it would seem they would both have much to gain from cooperation in the area of language recognition and translation.
As it has been the case for the past thirty years, the description of the prowesses of the system are still written in the conditional form: "...IBM technology can be used to control computers and devices..." rather than the active form: "is being used"...
Ben Shneiderman is the person who, in my opinion, articulates the best the limits of speech recognition.
One of my favorite phrases to explain this issue is: "You don't want to speak to a computer, because you can't speak and think at the same time". More precisely, speech utterance makes use of some modules in our brain which are required for planification too. Hence, you can't plan as well what to do next when you speak, which is a big hurdle in the type of intellectual activities one carries with a computer.
Speech-to-text is cool, but for 30 years they've been predicting it's the next new thing in interfaces, and it's remained a niche thing as it gets better and better. Maybe it'll hit the point where it's flawless and suddenly find new markets, but we'll see.
What really bothers me is the state of Windows text-to-speech. The TTS that ships with the most popular operating system on Earth is easily trumped in understandability by a small third-party program I downloaded literally TWELVE YEARS AGO. I really wonder if M$ made some pact to give out crappy TTS so as not to stifle sales of some business partner's application.
This seems pretty ridiculous, but I'm at a loss as to why their text-to-speech programs are of 12-year-old quality.
I'm glad people are doing good speech research, (I know I've seen a demo of good IBM TTS somewhere) but I hope it finds its way into Windows someday.
xkcd.com - a webcomic of mathematics, love, and language.
Of course it won't be open source. They achieved what they dub a "breakthrough in speech recognition". They plan on making a lot of money with this.
I realize that Anericans and British (English at least ;o)) speak essentially the same language but I have yet to find any speech recognition software that can get more than roughly 85% of what I say correct. I have a fairly soft neutral english accent with pretty good enunciation so I would have expectd to be getting a recognition rate in the high 90%s. I'm wondering if, as most of this software is developed in the US, it is tuned specifically to pick up on english with a US accent? I realize that you train the software for your voice but AIUI all you are doing is tuning a basic speech model. Has anyone else had this problem or is it just me?
I used to have a better sig but it broke.
I think it was about 1996 or maybe 1997 when I attended an IBM demonstration (for retailers) for its speech recognition software. Anyway, the lady who was narrating the text and. talking. like. a. robot. to. do. it. was half-way through when, for no apparent reason, the word uterus appeared in the text.
So I'm sitting here thinking of how funny it was to the juvenile me back then, and how unfunny it seems right now. Oh well.
It's been well-known among language researchers that both speech recognition and parsing/comprehension are much easier when applied to a small problem domain. SRI in Palo Alto and CSLI at Stanford, for example, have a number of very impressive speech recognition packages that understand, for example, medicine-related sentences. The dashboard controls just sound like a logical progression of this to faster computers and an even smaller problem domain. They're cool nonetheless.
The translation, on the other hand, sounds damned impressive. For unrestricted content, especially with an untrained voice (I imagine that IBM isn't individually training to each Al Jazeera talking head), 70% recognition sounds quite good. 70% accuracy post-translation ought to be quite a bit better than what's currently out there. The description of MASTOR, however, is useless -- it could easily describe anything that isn't word-for-word translation.
It is as closer to English as any other language. In general, European languages have the same basics as English (such as "the") and are fairly easy to learn and translate. Right now I live in Japan, where the language and its underlying way of thinking basically run in the reverse direction of English. To translate, you are essentially running the whole thing backwards. Worse yet, the fundamental parts of the language are quite different. For example, Japanese does not have articles or prepositions, though it has post-positions that roughly correspond. However, there are fewer of them, so they have "lots of meanings" when translated into English. Translation can be a "#$#, even for a human who understands both languages very well (which is why anime comes off so corny sometimes). There are countless times where there is just no simple way to express a thought in one language that is trivial in the other.
and it is usually extremely difficult to translate jokes. The senses of humor are quite different as well. I think this is part of the charm of anime, actually - we are laughing at things Japanese aren't always intended to find funny, while missing half of the jokes that are supposed to be there.
Speech recognition has long been the land of inflated promises and little returns. Anyone remember Lernout & Hauspie and its supposed 15 minutes learning time?
Speech recognition is riddled with problems. From a computing side it's enormously processor intensive and memory hungry. From a computer side it's very com,plex code and the 'learning' process is fraught with problems - surnames, company names and locations are all very poorly recognised.
So don't rush to buy. Let the labs check it out first.
There's a very good reason they're testing this tech on Arabic speech primarily. Although they won't say it, I'd be very surprised if the DOD isn't sponsoring this. NSA would absolutely love to be able to translate and transcribe monitored Arabic speech (ie, phone calls) in real time. No backlog of untranslated intercepts, no staff shortages.
I've actually never used any speech recognition software before today. That said, today just happens to be the day. That said, I tried out Dragon NaturallySpeaking for the first time, and it is a complete coincidence that this topic should come up. I'm actually dictating this post with Dragon, as we speak. ha ha
the training process definitely has its ups and downs. The more you work with it however, the more it becomes attenuated to your own speech patterns and moreover, the quirky words we use every day. If you can get past the first two or three hours, you'll see that it is totally worth the effort, especially if this IBM tech isn't available to end-users for some time. There is also an aspect of the software training you, while you train the software. At the present time, I can dictate to slightly slower than I can probably type.
In the end, I can see where this would make a writing e-mails and other such time-consuming tasks, which involve spellchecking, grammar, and other proof reading significantly quicker. When you really hit your stride, it's easy to write at the speed of thought, which is really appealing. There are caveats, however. it's very easy to dictate several sentences worth of tax and taken for granted that it to everything down the way you attendedselect tax select select tax undo
Although most of the discussion so far has focused on foreign language translation, this technology is about *real-time-audio-to-text* conversion. The feds will be able to monitor, analyze, and record our conversations in real time:
Monitor all conversation.
Apply real-time text filters.
Assign live agents to priority eavesdropping.
Profit!
If you could apply a filter to listen in to any call what would it be?
Be heard || Be herd
I was in Kuwait and watched arab TV with english subtitles, it was enlightening to say the least. One long tribute to racism paid for by the Amir of Quatar. Only on arab TV will you see such trash as "the jews are descended from pigs".
ViaVoice Embedded, the product that they're releasing, works on limited-domain problems: for example, tasks related to control of your car's peripherals. When the vocabulary and grammars are constrained it's possible to acheive very decent accuracy.
Dictation, however, is a completely different problem. There are far fewer constraints on what can be said, and the system makes errors as it picks through the possible choices. As a result, most dictation software requires training: the system will use your voice to train its recognition models to improve its word selection. Dictation systems also ask for samples of your documents to train its language models on how you put words together; that also helps determine the probabiity of proper word choice. (Example of how you put words together: "Peanut butter sandwich" is a much more likely choice than "peanut butter sand," and will get a higher score.)
The IBM announcement is about embedded, task-oriented speech recognition. It's not "superhuman," according to the article's text and ignoring its headline. I'll have an opportunity to see it in action next week at SpeechTek West. Expect to see other product announcements about speech technology in the next few days as the conference approaches.
As for the TV translation software, it's still in the research stage according to the article. I've seen BBN's version of this software, and frankly it's amazing how good real-time translation can be.
Bell Canada deployed Emily a few years back, and the results to date have been excellent. A top-level question of "How can I help you?" replaces several layers of DTMF auto-attendant complexity.
If you're interested in trying speech recognition and text-to-speech out for yourself, you can use Voxeo's servers, program in VoiceXML, and my Voice Conference Manager app as a starting point (yeah, VCM needs a new release, and it's getting one soon).
When and if it can translate poems from language to language, while keeping the style, the nuances, the rythm, the cultural references, the general idea and the details, then we will know - it is done. Until then, don't hold your breath.
You can't handle the truth.
Patriotic. What part of "*International* Business Machines" did you not understand? More likely it's to show that they really understand the problem and not just the English-only subset.
this of course worries secretaries, since they might eventually lose their job/"career". on the other hand it would improve effeciency *a lot*.
There's nothing too profound behind this sig.
I can wreck a nice beach. I can recognize speech.
Well, Dragon Systems eight passed the beach test first try. Knowing the program, however, I did use pretty clear diction.
I use Dragon Systems and find it absolutely great. There are a few persistent errors. For example, It frequently fails to get "there" and " there" right on the first try. But the fly down menu system enables me to quickly correct the problem on the run. Certainly I pick it up on an edit. If IBM has something better than this -- and it sounds like they do -- then it must be pretty darn good. Of course, you have to insert the punctuation verbally. But that comes with a little practice -- provided that you know what to do in the first place.
It does take a little bit of investment in time. But not nearly as much as learning to type at seventy words a minute, which I can now do in dictation. I have added very little by way of customized commands etc. The program has done a lot of learning on its own.
Let's try once again: I can't recognize beach. I can recognize speech. Oops. Okay, it failed that time. Let's try one more time: I can wreck a nice beach. I can recognize speech. Well, the phrases have to be enunciated pretty clearly or the program has trouble.
Which which blew the blue candle. Failed on the second "which" the b*tch.
Okay, okay. I'll put the laundry in the dryer. No I am not just screwing around on Slashdot again I'm getting some work done down here. Just a minute. Just a MINUTE.
One trouble. You do have to put the mike to sleep during family discussions.
"No fear. No envy. No meanness." Liam Clancy
Transcription? Not too hard. Translation? I highly doubt it.
Recent studies of the efficacy of machine translation found that we have made only marginal progress by modern engines from those of the *70s*, (in fact, one of them, SysTrans, is the most used translation engine online) and there were *no* descernable difference between engines of the eighties and current engines. I hope that they're not trying to claim that they suddenly overcame the vast problems of translation wholly independent of the linguistic community. That's just ludicrous.
I'd love to see the this engine handle a parasitic sentence like this between two largely different languages and catch the nuance in the parens: "Which report did she file (that report) without (her) reading (that same report)?" Sure some engines will hit by chance, but only because of similar structure, but the engine is lucky, not actually parsing the "meaning."
"Fight for lost causes. You may discover they weren't."