# Inside Outside algorithm

This is a Method page for the Inside-outside algorithm.

## Contents |

## Background

The inside-outside algorithm is a way of estimating probabilities in a PCFG. It is first introduced Baker (1979). The inside outside algorithm is in fact a generalization of the forward-backward algorithm (for hidden Markov models) to PCFGs.

It is mainly used for unsupervised parsing. For references to parsing related papers, refer to Class meeting for 10-710

## Algorithm

The algorithm is a dynamic programming algorithm that is often used with chart parsers to estimate expected production counts. Here, we assume the grammar is of Chomsky Normal Form.

The algorithm works by computing 2 probabilities for each nonterminal and span .

### Inside probabilities

The inside probability is defined as , which is the probability of a nonterminal generating the word sequence to .

The inside probability can be calculated recursively with the following recurrence relation:

Intuitively, this can be seen as computing the sum over all possible ways of building trees rooted by and generating the word span .

For the base case, it is simply .

### Outside counts

The outside probability is defined as , which is the probability of generating a parse tree spanning the entire sentence that uses nonterminal to span .

The reccurrence relation is thus:

The first term is basically considering all ways of generating trees where is used as a right subtree, and vis a vis for the second term.

### Dynamic programming: Putting them together

In a standard EM framework, we would want to compute for each production rule, the expected number of times it is used for a given sentence, which we can compute by summing over the counts of using the production for all possible spans (and separation points)

The new estimated production probabilities would thus be

## Complexity

For a given sentence of length and grammar , the inside outside algorithm is

## References

Trainable grammars for speech recognition. J Baker (1979). The original paper introducing the inside-outside algorithm

Notes on Inside-Outside algorithm. Jason Eisner. provides a good walkthrough and explanation on using the inside-outside algorithm with a PCFG

A Derivation of the Inside-Outside Algorithm from the EM Algorithm. John D Lafferty (2000). shows the the inside-outside algorithm as a special case of EM, and proves its convergence.