cs60057 speech &natural language processing

Lecture 1, 7/21/2005 Natural Language Processing 1

CS60057Speech &Natural Language

Processing

Autumn 2007

Lecture4

1 August 2007


MORPHOLOGY


Finite State Machines

FSAs are equivalent to regular languages FSTs are equivalent to regular relations (over pairs of

regular languages) FSTs are like FSAs but with complex labels. We can use FSTs to transduce between surface and

lexical levels.


Simple Rules


Adding in the Words


Derivational Rules


Parsing/Generation vs. Recognition

Recognition is usually not quite what we need. Usually if we find some string in the language we need

to find the structure in it (parsing) Or we have some structure and we want to produce a

surface form (production/generation) Example

From “cats” to “cat +N +PL” and back


Morphological Parsing

Given the input cats, we’d like to outputcat +N +Pl, telling us that cat is a plural noun.

Given the Spanish input bebo, we’d like to outputbeber +V +PInd +1P +Sg telling us that bebo is the present indicative first person singular form of the Spanish verb beber, ‘to drink’.


Morphological Anlayser

To build a morphological analyser we need: lexicon: the list of stems and affixes, together with basic information

about them

morphotactics: the model of morpheme ordering (eg English plural morpheme follows the noun rather than a verb)

orthographic rules: these spelling rules are used to model the changes that occur in a word, usually when two morphemes combine (e.g., fly+s = flies)


Lexicon & Morphotactics

Typically list of word parts (lexicon) and the models of ordering can be combined together into an FSA which will recognise the all the valid word forms.

For this to be possible the word parts must first be classified into sublexicons.

The FSA defines the morphotactics (ordering constraints).


Sublexicons to classify the list of word parts

reg-noun irreg-pl-noun irreg-sg-noun plural

cat mice mouse -s

fox sheep sheep

geese goose


FSA Expresses Morphotactics (ordering model)


Towards the Analyser

We can use lexc or xfst to build such an FSA

To augment this to produce an analysis we must create a transducer Tnum which maps between the lexical level and an "intermediate" level that is needed to handle the spelling rules of English.


Three Levels of Analysis


1. Tnum: Noun Number Inflection

• multi-character symbols• morpheme boundary ^• word boundary #


Intermediate Form to Surface

The reason we need to have an intermediate form is that funny things happen at morpheme boundaries, e.g.cat^s catsfox^s foxesfly^s flies

The rules which describe these changes are called orthographic rules or "spelling rules".


More English Spelling Rules

consonant doubling: beg / begging y replacement: try/tries k insertion: panic/panicked e deletion: make/making e insertion: watch/watches Each rule can be stated in more detail ...


Spelling Rules

Chomsky & Halle (1968) invented a special notation for spelling rules.

A very similar notation is embodied in the "conditional replacement" rules of xfst.

E -> F || L _ Rwhich means replace E with F when it appears between left context L and right context R


A Particular Spelling Rule

This rule does e-insertion

^ -> e || x _ s#


e insertion over 3 levels

The rule corresponds to the mapping betweensurface and intermediate levels


e insertion as an FST


Incorporating Spelling Rules

Spelling rules, each corresponding to an FST, can be run in parallel provided that they are "aligned".

The set of spelling rules is positioned between the surface level and the intermediate level.

Parallel execution of FSTs can be carried out: by simulation: in this case FSTs must first be aligned. by first constructing a a single FST corresponding to their

intersection.


Putting it all together

execution of FSTi

takes place in parallel


Kaplan and Kay: The Xerox View

FSTi are alignedbut separate

FSTi intersectedtogether


Finite State Transducers

The simple story Add another tape Add extra symbols to the transitions

On one tape we read “cats”, on the other we write “cat +N +PL”, or the other way around.


FSTs


English Plural

surface lexical

cat cat+N+Sg

cats cat+N+Pl

foxes fox+N+Pl

mice mouse+N+Pl

sheep sheep+N+Pl

sheep+N+Sg


Transitions

c:c means read a c on one tape and write a c on the other +N:ε means read a +N symbol on one tape and write nothing on the

other +PL:s means read +PL and write an s

c:c a:a t:t +N:ε +PL:s


Typical Uses

Typically, we’ll read from one tape using the first symbol on the machine transitions (just as in a simple FSA).

And we’ll write to the second tape using the other symbols on the transitions.


Ambiguity

Recall that in non-deterministic recognition multiple paths through a machine may lead to an accept state. Didn’t matter which path was actually traversed

In FSTs the path to an accept state does matter since differ paths represent different parses and different outputs will result


Ambiguity

What’s the right parse for Unionizable Union-ize-able Un-ion-ize-able

Each represents a valid path through the derivational morphology machine.


Ambiguity

There are a number of ways to deal with this problem Simply take the first output found Find all the possible outputs (all paths) and return

them all (without choosing) Bias the search so that only one or a few likely paths

are explored


The Gory Details

Of course, its not as easy as “cat +N +PL” <-> “cats”

As we saw earlier there are geese, mice and oxen But there are also a whole host of spelling/pronunciation

changes that go along with inflectional changes Cats vs Dogs Fox and Foxes


Multi-Tape Machines

To deal with this we can simply add more tapes and use the output of one tape machine as the input to the next

So to handle irregular spelling changes we’ll add intermediate tapes with intermediate symbols


Generativity

Nothing really privileged about the directions. We can write from one and read from the other or vice-

versa. One way is generation, the other way is analysis


Multi-Level Tape Machines

We use one machine to transduce between the lexical and the intermediate level, and another to handle the spelling changes to the surface tape


Lexical to Intermediate Level


Intermediate to Surface

The add an “e” rule as in fox^s# <-> foxes#


Foxes


Note

A key feature of this machine is that it doesn’t do anything to inputs to which it doesn’t apply.

Meaning that they are written out unchanged to the output tape.

Turns out the multiple tapes aren’t really needed; they can be compiled away.


Overall Scheme

We now have one FST that has explicit information about the lexicon (actual words, their spelling, facts about word classes and regularity). Lexical level to intermediate forms

We have a larger set of machines that capture orthographic/spelling rules. Intermediate forms to surface forms


Overall Scheme


http://nltk.sourceforge.net/index.php/Documentation

cs60057 speech &natural language processing

Documents

spelling rules of english

verborthographic rules

s fliesthe rules

word boundary

conditional replacement

model of morpheme ordering

english plural morpheme

valid word forms