Can Computers Talk?
This is known as “speech synthesis ”translate text to phonetic forme.g., “fictitious ” -> fik-tish-e use pronunciation rules to map phonemes to actual sound
* e.g., “tish ” -> sequence of basic audio sounds
sounds made by this “lookup ” approach sound unnatural
sounds are not independent e.g., “act ” and “action ” modern systems (e.g., at AT&T) can handle this pretty well a harder problem is emphasis, emotion, etc humans understand what they are saying machines don ’t: so they sound unnatural
- NO, for complete sentences
- YES, for individual words
Can Computers Recognize Speech?
mapping sounds from a microphone into a list of words
classic problem in AI, very difficult “ Lets talk about how to wreck a nice beach”
* (I really said “________________________ ”)
Recognizing single words from a small vocabulary systems can do this with high accuracy (order of 99%)
* e.g., directory inquiries
limited vocabulary (area codes, city names)
computer tries to recognize you first, if unsuccessful hands you over to a human operator
* saves millions of dollars a year for the phone companies
* Recognizing normal speech is much more difficult
* speech is continuous: where are the boundaries between words?
* e.g., “John ’s car has a flat tire ”
* large vocabularies
* can be many thousands of possible words
* we can use context to help figure out what someone said
* e.g., hypothesize and test
*try telling a waiter in a restaurant:
“I would like some dream and sugar in my coffee”
* background noise, other speakers, accents, colds, etc
* on normal speech, modern systems are only about 60-70% accurate
* NO, normal speech is too complex to accurately recognize
* YES, for restricted problems (small vocabulary, single speaker)
Can Computers Understand speech?
* Understanding is different to recognition:
* “ Time flies like an arrow”
* assume the computer can recognize all the words
* how many different interpretations are there?
* 1. time passes quickly like an arrow?
* 2. command: time the flies the way an arrow times the flies
* 3. command: only time those flies which are like an arrow
* 4. “time-flies” are fond of arrows
* only 1. makes any sense,
* but how could a computer figure this out?
* clearly humans use a lot of implicit commonsense knowledge in communication
* Conclusion: NO, much of what we say is beyond the capabilities of a computer to understand at present
Can Computers Learn and Adapt?
* Learning and Adaptation
* consider a computer learning to drive on the freeway
* we could teach it lots of rules about what to do
* or we could let it drive and steer it back on course when it heads for the embankment
* systems like this are under development (e.g., Daimler Benz)
* e.g., RALPH at CMU
* in mid 90 ’s it drove 98% of the way from Pittsburgh to San Diego without any human assistance
* machine learning allows computers to learn to do things without explicit programming
* many successful applications:
* requires some “set-up” : does not mean your PC can learn to forecast the stock market or become a brain surgeon
Conclusion: YES, computers can learn and adapt, when presented with information in the appropriate way
Can Computers “see”?
* Recognition v. Understanding (like Speech)
* Recognition and Understanding of Objects in a scene
* look around this room
* you can effortlessly recognize objects
* human brain can map 2d visual image to 3d “map”
Why is visual recognition a hard problem?
* mostly NO: computers can only “see ” certain types of objects under limited circumstances
* YES for certain constrained problems (e.g., face recognition)
Can computers plan and make optimal decisions?
* involves solving problems and making decisions and plans
* e.g., you want to take a holiday in Brazil
* you need to decide on dates, flights
* you need to get to the airport, etc
* involves a sequence of decisions, plans, and actions
* What makes planning hard?
* the world is not predictable:
* your flight is canceled or there ’s a backup on the 405
* there are a potentially huge number of details
* do you consider all flights? all dates?
* no: commonsense constrains your solutions
* AI systems are only successful in constrained planning problems
* Conclusion: NO, real-world planning and decision-making is still beyond the capabilities of modern computers
* exception: very well-defined, constrained problems