# Finite State Transducers

A DFA, on input a string, produces a single bit answer: accept or reject. Here we define a more general kind of finite automata (Finite State Transducers or FST), often useful in applications, that can produce arbitrarily long strings as output. Moreover, the output is produced in a streaming fashion, reading the input in a single pass, and producing the output string on the fly.

There are several possible ways to formalize FSTs as a mathematical definition or a computer program. Here we choose to define FSTs by modifying our definition of DFA as follows:

• Beside the usual input alphabet Σ, we also specify an output alphabet Γ, so that FSTs can be used to convert strings between different character sets.
• Instead of a set of final states F ⊆ Q, we specify an output function γ : Q → Γ * , which at every state q produces γ(q) as part of the output string.

In summary, an FST is a define by a tuple T = (Q, Σ, Γ, δ, s, γ) where Q, Σ, δ, s are just as in the definition of DFAs, Γ is a finite alphabet, and γ : Q → Γ *  is a function. As for DFAs, we make the definition of FST parametric with respect to the type of state, and define a function evalFST that maps each FST T to the corresponsing function fT : Σ *  → Γ * , the function computed by T.

import DFA (extendDelta)

type FST st = ([st],[Char],[Char],st->Char->st,st,st->String)

evalFST :: FST st -> String -> String
evalFST (qs,sigma,gamma,delta,s,out) [] = out s
evalFST (qs,sigma,gamma,delta,s,out) (x:xs) =
let s1 = delta s x
fst1 = (qs,sigma,gamma,delta,delta s x,out)
in (out s) ++ (evalFST fst1 xs)

The first line imports the extendDelta function from the DFA module, as we will need it later on. Since the transition function δ of an FST has the same type as the transition funciton of a DFA, we can apply extendDelta to it.

Let's define two example FSTs, and try out our evaluation function. For convenience, we define bits as an abbreviation for the binary alphabet. The first FST flips all the bits. The second FST removes repeted occurrences of 0.

bits = ['0','1']

flipFST = ([0,1,2],bits,bits,delta,2,out) where
delta q '0' = 1
delta q '1' = 0
out 0 = "0"
out 1 = "1"
out 2 = ""

data ABCD = A | B | C | D

nodup0FST = ([A,B,C,D],bits,bits,delta,A,out) where
delta A '0' = C
delta B '0' = C
delta _ '0' = D
delta _ '1' = B
out A = ""
out B = "1"
out C = "0"
out D = ""
ghci> evalFST flipFST "000111001101"
"111000110010"
ghci> evalFST nodup0FST "000111001101"
"011101101"

As you may expect, FSTs can be composed together: given two FSTs T0 and T1, we can combine them into a single FST that computes the function composition (T1 ∘ T0)(x) = T1(T0(x)).

composeFST :: FST st1 -> FST st0 -> FST (Maybe (st0,st1))
composeFST (qs1,sigma1,gamma1,delta1,s1,out1)
(qs0,sigma0,gamma0,delta0,s0,out0) | (gamma1 == sigma0)
= (qs,sigma0,gamma1,delta,Nothing,out)
where qs = [Nothing] ++ [Just (q0,q1) | q0 <- qs0, q1 <- qs1]
delta Nothing x = delta (Just (s0,s1)) x
delta (Just (q0,q1)) x =
Just (delta0 q0 x, (extendDelta delta1) q1 (out0 q0))
out Nothing =
let fst1 = (qs1,sigma1,gamma1,delta1,s1,out1)
in evalFST fst1 (out0 s0)
out (Just (q0,q1)) =
let fst1 = (qs1,sigma1,gamma1,delta1,q1,out1)
n = length (out1 q1)
in drop n (evalFST fst1 (out0 q0))

Let us go over the definition one piece at a time. We define the set of states of the composed transducer as the cartesian product of the sets of states of T0 and T1, plus a new (start) state. A simple way to add a new state to st is to use the type Maybe st. We have already seen the Maybe type constructor, which is typically used to represent an optional value of some type. Here we use Maybe just as a trick to introduce a new state Nothing, in addition to all the old states Just (q0,q1).

The transition function delta and output function out are defined for this new set of states. The transition function δ treats the new start state Nothing identically to the pair of start states Just (s0,s1). In general, on input a symbol x the current state of the transducer Just (q_0,q_1) is updated by letting the first transducer read x, and the second transducer read the string out0 q0 produced by the first transducer before reading the x.

The output function is defined using evalFST. Let us first look at the output associated to the start state Nothing. On input the empty string ϵ, the first transducer produces a string out0 s0, which is passed to the second transducer. So, the final output can be computed as the output of the second transducer fst1 on input out0 s0. The output function on other states is defined similarly, except that we use a transducer fst1 with propertly modified start state q1, and we remove the first n characters of the output to avoid duplications.

Time to try out our composition function. Let us start with something simple: flipping a string twice:

ghci> evalFST (composeFST flipFST flipFST) "01010011"
"01010011"

Now, say we want to define a transducer nodup1 that removes all the repeated occurrences of the bit 1. We could define it from scratch, similarly to the definition of nodup0. But an even simpler solution can be obtained by reusing nodup0 in combination with the flip transducer: we first flip all the bits, remove repeated 0s, and then flip the bits again.

ghci> let nodup1FST = flipFST `composeFST` nodup0FST `composeFST` flipFST
ghci> evalFST nodup1FST "000111001101"
"000100101"

For future reference, you can find the code with the definition of FST, evaluation and composition functions at FST.hs. The example FSTs are in lec3.hs.