SEL1007: The Nature of Language Computation, mind, and language: the history of 20 th Century linguistics 1
Jan 06, 2016
SEL1007: The Nature of Language
Computation, mind, and language: the history of 20th Century linguistics
1
The plan for today
A bit of history: the classical mind-body problem
Computers as a solution Language and the theory of
computers
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)
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
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
The ‘mind/body problem’
So what “causes” free will? Descartes’ (perfectly scientific) response: substance dualism There’s two kinds of ‘stuff’ in the universe
But modern science not so keen on substance dualism
A more modern solution:
=
Why is this helpful for the scientific study of language? Computers provide an acceptable
metaphor. Mental operations (like thought, or
language) 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
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
Computers transform strings of symbols into other strings via an algorithm
Alan Turing (1912-1954)
Some fundamental concepts
Symbols (and symbol systems) Any physical thing which, by agreement,
represents something else
= USA
The relevant symbol system
Another symbol: p (represents /p/) The symbol system: the Roman alphabet
More fundamental concepts
Strings A series of symbols taken from a
particular symbol system abcde, aakkklubss, powerpointsucks,
banana
More fundamental concepts
Algorithms A sequence of instructions to perform
particular tasks in a particular order
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 rightNote: Each step is explicit and the steps are in a particular order
Another kind of algorithm: recipes
OK, so what do computers do?
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
An example of a ‘Turing Machine’
Doing “1+1=2” with a Turing Machine
Doing “1+1=2” with a Turing Machine
Doing “1+1=2” with a Turing Machine
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.
A phrase-structure grammar of (a very small part of)
EnglishS -> NP VP Det -> theNP -> N VP -> V NPNP -> Det N V -> bitesN -> man V -> catchesN -> dogN -> cat
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 VPS -> the N VPS-> the man VP
Language Generation
the man V NPthe man bites NPthe man bites Det Nthe man bites the Nthe man bites the dog
Et voila!
Understanding language using a phrase-structure
grammar
The man bites the dog
Det N V Det N
NP NP
VP
S
But….It’s important to keep two questions separate
The technologyquestion
The natural worldquestion
≠[from http://www.learnfrenchlab.com/how-to-speak-french.html]
[from http://motherboard.vice.com/2010/8/5/eight-sci-fi-robots-that-prove-that-robots-aren-t-going-to-enslave-humanity]
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.
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) 吃飯 = 把嘴裡的食物
If the mind is just a computer, then there’s a problem. Human beings must be doing something more.
Next Time
A different 20th century reaction:
Run away! Run away!