bleu_sentence_ids {sacRebleu}

Computes BLEU-Score (Papineni et al., 2002).

Description

'bleu_sentence_ids' computes the BLEU score for a single candidate sentence and a list of reference sentences. The sentences must be tokenized before so they are represented as integer vectors. Akin to 'sacrebleu' ('Python'), the function allows the application of different smoothing methods. Epsilon- and add-k-smoothing are available. Epsilon-smoothing is equivalent to 'floor' smoothing in the sacrebleu implementation. The different smoothing techniques are described in Chen et al., 2014 (https://aclanthology.org/W14-3346/).

Usage

bleu_sentence_ids(
  references,
  candidate,
  n = 4,
  weights = NULL,
  smoothing = NULL,
  epsilon = 0.1,
  k = 1
)

Arguments

references

A list of reference sentences.

candidate

A candidate sentence.

n

N-gram for BLEU score (default is set to 4).

weights

Weights for the n-grams (default is set to 1/n for each entry).

smoothing

Smoothing method for BLEU score (default is set to 'standard', 'floor', 'add-k' available)

epsilon

Epsilon value for epsilon-smoothing (default is set to 0.1).

k

K value for add-k-smoothing (default is set to 1).

Value

The BLEU score for the candidate sentence.

Examples

ref_corpus <- list(c(1,2,3,4))
cand_corpus <- c(1,2,3,5)
bleu_standard <- bleu_sentence_ids(ref_corpus, cand_corpus)
bleu_floor <- bleu_sentence_ids(ref_corpus, cand_corpus, smoothing="floor", epsilon=0.01)
bleu_add_k <- bleu_sentence_ids(ref_corpus, cand_corpus, smoothing="add-k", k=1)