1 / 28

SEL1007: The Nature of Language

SEL1007: The Nature of Language. Computation , mind, and language: the history of 20 th Century l inguistics 1. The plan for today. A bit of history: the classical mind-body problem How computers work Language and the theory of computers.

venice
Download Presentation

SEL1007: The Nature of Language

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. SEL1007: The Nature of Language Computation, mind, and language: the history of 20th Century linguistics 1

  2. The plan for today • A bit of history: the classical mind-body problem • How computers work • Language and the theory of computers

  3. Descartes and the scientific study of language and mind • “I think, therefore I am” • Invented the Cartesian coordinate system and analytic geometry • Formulated the ‘mind/body problem’ René Descartes (1596-1650)

  4. The ‘mind/body problem’ • The world (and the animal kingdom) are basically big machines • But human beings are different • Human behavior is neither completely deterministic nor completely random • In other words, human beings have free will

  5. The ‘mind/body problem’ • Language is an important facet of this “it is quite remarkable that there are no men so dull-witted and stupid…that they are incapable of arranging various words together and forming an utterance from them in order to make their thoughts understood; whereas there is no other animal, no matter how perfect and well endowed it may be, that can do the same.” -Discourse on Method

  6. The ‘mind/body problem’ • Descartes’ (perfectly scientific) response: substance dualism • There’s two kinds of ‘stuff’ in the universe • But modern science not so keen on substance dualism

  7. Modern science’s reply

  8. In other words… =

  9. Why is this helpful for the scientific study of language? • Computers provide an acceptable metaphor. • Mental operations (like thought) aren’t some mystical incomprehensible thing. It’s ‘just like’ what a computer is doing • The hardware/software distinction • People had a theory of how computers worked

  10. So, how does a computer work exactly? • Key member of Bletchley Park team that broke the Nazi “Enigma” code • His formulation of ‘what a computer is’ underlies most of modern computer science and computer technology Alan Turing (1912-1954)

  11. Some fundamental concepts • Symbols (and symbol systems) • Any physical thing which, by agreement, represents something else = USA

  12. The relevant symbol system • Another symbol: p (represents /p/) • The symbol system: the Roman alphabet

  13. More fundamental concepts • Strings • A series of symbols taken from a particular symbol system • abcde, aakkklubss, powerpointsucks, banana

  14. More fundamental concepts • Algorithms • A sequence of instructions to perform particular tasks in a particular order

  15. An algorithm for getting from the School Office to the Student Union • Go through the double doors to the landing • Go down the stairs to the ground floor • Exit the Percy Building from the main entrance • Walk down the quad • Walk under the arches • Cross the road • Walk 10 metres straight ahead • Turn right Note: Each step is explicit and the steps are in a particular order • Another kind of algorithm: recipes

  16. More fundamental concepts • Computation • = string transformation • String 1 = (2+2)/3; String 2 = 1.333333 • String 1 = ‘the car’; String 2 = ‘el coche’ • The computer transforms one string into another by following the algorithm

  17. An example of a ‘Turing Machine’

  18. Doing “1+1=2” with a Turing Machine

  19. Doing “1+1=2” with a Turing Machine

  20. Doing “1+1=2” with a Turing Machine

  21. Language as string transformation: a phrase-structure grammar • A grammar = an algorithm for producing and understanding language • ‘phrase-structure’ = sequences of words are structured as/consist of phrases.

  22. A phrase-structure grammar of (a very small part of) English S -> NP VP Det -> the NP -> N VP -> V NP NP -> Det N V -> bites N -> man V -> catches N -> dog N -> cat

  23. Language Generation S -> NP VP • Two restrictions on rewriting • Only rewrite one symbol at a time • Only the leftmost symbol can be rewritten S -> Det N VP S -> the N VP S-> the man VP

  24. Language Generation the man V NP the man bites NP the man bites Det N the man bites the N the man bites the dog • Et voila!

  25. Understanding language using a phrase-structure grammar S VP NP NP Det N V Det N The man bites the dog

  26. But…. It’s important to keep two questions separate The technology question The natural world question ≠ [from http://motherboard.vice.com/2010/8/5/eight-sci-fi- robots-that-prove-that-robots-aren-t-going-to-enslave-humanity [from http://www.learnfrenchlab.com/how-to- speak-french.html]

  27. Not doing too badly with the first one (but see YouTube, etc.) • Little more of a problem with the second one • Phrase-structure grammars don’t have the right mathematical properties for natural language • Most successful language parsers require some degree of initial ‘training’ (via a corpus of pre-parsed sentences). Children don’t.

  28. Also, the ‘symbol grounding’ problem • Computers manipulate symbols, but they don’t understand them (imagine trying to learn Chinese from a Chinese dictionary of Chinese) • If the mind is just a computer, then there’s a problem. Human beings must be doing something more.

More Related