NgramLanguageModel

Type Parameters:

W -

All Known Subinterfaces:

ArrayEncodedNgramLanguageModel<W>, ContextEncodedNgramLanguageModel<W>

All Known Implementing Classes:

AbstractArrayEncodedNgramLanguageModel, AbstractContextEncodedNgramLanguageModel, AbstractNgramLanguageModel, ArrayEncodedCachingLmWrapper, ArrayEncodedProbBackoffLm, ContextEncodedCachingLmWrapper, ContextEncodedProbBackoffLm, KneserNeyLmReaderCallback, StupidBackoffLm
```
public interface NgramLanguageModel<W>
```
Base interface for an n-gram language model, which exposes only inefficient convenience methods. See ContextEncodedNgramLanguageModel and ArrayEncodedNgramLanguageModel for more efficient accessors.

Author:

adampauls

Nested Class Summary

Nested Classes
Modifier and Type Interface Description

static class NgramLanguageModel.StaticMethods

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`int`	`getLmOrder()`	Maximum size of n-grams stored by the model.
`float`	`getLogProb(java.util.List<W> ngram)`	Scores an n-gram.
`WordIndexer<W>`	`getWordIndexer()`	Each LM must have a WordIndexer which assigns integer IDs to each word W in the language.
`float`	`scoreSentence(java.util.List<W> sentence)`	Scores a complete sentence, taking appropriate care with the start- and end-of-sentence symbols.
`void`	`setOovWordLogProb(float logProb)`	Sets the (log) probability for an OOV word.

- Method Detail
  - getLmOrder
```
int getLmOrder()
```
    Maximum size of n-grams stored by the model.
    
    Returns:
  - getWordIndexer
```
WordIndexer<W> getWordIndexer()
```
    Each LM must have a WordIndexer which assigns integer IDs to each word W in the language.
    
    Returns:
  - scoreSentence
```
float scoreSentence(java.util.List<W> sentence)
```
    Scores a complete sentence, taking appropriate care with the start- and end-of-sentence symbols. This is a convenience method and will generally be inefficient.
    
    Returns:
  - getLogProb
```
float getLogProb(java.util.List<W> ngram)
```
    Scores an n-gram. This is a convenience method and will generally be relatively inefficient. More efficient versions are available in ArrayEncodedNgramLanguageModel.getLogProb(int[], int, int) and ContextEncodedNgramLanguageModel.getLogProb(long, int, int, edu.berkeley.nlp.lm.ContextEncodedNgramLanguageModel.LmContextInfo) .
  - setOovWordLogProb
```
void setOovWordLogProb(float logProb)
```
    Sets the (log) probability for an OOV word. Note that this is in general different from the log prob of the unk tag probability.