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Language Processing Technology Machines and other artefacts that use language.

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1 Language Processing Technology Machines and other artefacts that use language

2 April 2002 Language and Computers HAL The computer in 2001: A Space Odyssey could: Speak and understand English. Recognize speech. Read lips… HAL doesn’t exist yet, but there is hope (maybe this decade).

3 April 2002 Language and Computers HAL’s capabilities “Open the pod bay doors please, HAL” “I’m sorry Dave, I’m afraid I can’t do that”

4 April 2002 Language and Computers Speech recognition HAL must be able to analyze the speech signal and work out which words were said. Needs to know about phonetics and phonology.

5 April 2002 Language and Computers Speech synthesis HAL needs to be able to take a series of words and pronounce it naturally and fluently. Use contractions “I’m sorry”, not “I am sorry” Needs to get rhythm and intonation right.

6 April 2002 Language and Computers Methods for speech synthesis By imitation of articulator movements (very flexible) By stringing together units (easy to achieve naturalness) Phones (simplest) Diphones (captures co-articulation) Larger units (can be very accurate)

7 April 2002 Language and Computers Part of speech tagging Current computational linguistics can handle the task of assigning parts of speech to words. HAL does this, presumably, but this is really just a step along the way to syntax.

8 April 2002 Language and Computers Syntax HAL understood that the request was a request. It was “open the pod bay doors HAL” It wasn’t “the pod bay doors are open” It wasn’t “are the pod bay doors open?” It wasn’t “could you open the pod bay doors?” To do that, we need syntax (which forms groups of words)

9 April 2002 Language and Computers Semantics HAL has to know that the request is about the pod bay doors (not Dave’s breakfast) It has to know lexical semantics – what kind of thing the word “doors” can refer to. It also has to know compositional semantics – how to put the meanings of “pod”,”bay” and “doors” together to get the right composite meaning.

10 April 2002 Language and Computers Pragmatics HAL could have said “No” Instead it said “I’m sorry”, “I’m afraid…” and “I can’t” Would have been more truthful to say “I won’t”. But the correct use of polite and indirect language is usual for humans. Human listeners realize that HAL refused.

11 April 2002 Language and Computers Discourse conventions HAL could have just failed to reply. Human conversation requires and expects that we engage in structured interactions. HAL correctly uses the word “that” to refer to the topic raised by Dave. Correctly structuring such conversations requires HAL to know when to speak and when to listen.

12 April 2002 Language and Computers HAL overview Speech synthesis Speech recognition Syntax Lexical semantics oCompositional semantics oDiscourse and pragmatics

13 April 2002 Language and Computers Real world applications Can’t do HAL (yet), but can do various useful things with more limited abilities. Most of these rely on good choice of a task. Suitable tasks involve something that computers do better (or much faster) than people do. Language is in service of the task, not the other way round.

14 April 2002 Language and Computers Information retrieval Given a (perhaps huge) collection of documents and a user need expressed as a query, present the most relevant documents. Query “pod bay door malfunction” Response – a ranked list of documents Technology is essentially glorified word counting.

15 April 2002 Language and Computers Text categorization Given a text and a set of categories, assign the text to a categories Here’s an message, is it Junk mail About sailing boats A rant from alt.atheism or comp.sys.ibm.pc Technology relies on sophisticated weighting of evidence.

16 April 2002 Language and Computers Information extraction Given hundreds of articles, find information (not just documents) of interest. “John Smith joined the board of IBM as chairman” {IN=“John Smith”; POST=“chairman”; COMPANY=“IBM”} Technology is syntactic parsing plus lots of task specific tricks.

17 April 2002 Language and Computers Machine translation Take a sentence in English and put it into (for example) Japanese. Very demanding: requires all HAL’s levels plus a sophisticated understanding of literary style. But commercial and research systems exist which can “Gloss” a passage producing something that a human translator can adapt. Technology is usually word-to-word models with good bilingual dictionaries but limited syntax and some smarts for choosing between alternatives.

18 April 2002 Language and Computers Dialog systems You phone up a system and talk to it. It listens, talks back and does something for you. Tourist information, airline bookings. Your assignment for next time is to imagine a travel plan, phone CMU- PLAN ( ), which is toll-free, and pretend to book a flight.


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