Nltk 计算整个语料库的meteor_分数

据我所知，

meteor_score

来自

nltk.translate.meteor_score

根据候选列表计算一个假设句子的meteor得分

但是，是否有一种计算整个语料库得分的实现，或者有一种类似于

corpus\u bleu

实现的方法

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我找不到这个案子的证据

我为我的项目创建了如下内容：

#>>> nltk.download()
# Download window opens, fetch wordnet
#>>> from nltk.corpus import wordnet as wn
from nltk.translate.meteor_score import meteor_score


import numpy as np

def corpus_meteor(expected, predicted):
    meteor_score_sentences_list = list()
    [meteor_score_sentences_list.append(meteor_score(expect, predict)) for expect, predict in zip(expected, predicted)]
    meteor_score_res = np.mean(meteor_score_sentences_list)
    return meteor_score_res

---

我为我的项目创建了如下内容：

#>>> nltk.download()
# Download window opens, fetch wordnet
#>>> from nltk.corpus import wordnet as wn
from nltk.translate.meteor_score import meteor_score


import numpy as np

def corpus_meteor(expected, predicted):
    meteor_score_sentences_list = list()
    [meteor_score_sentences_list.append(meteor_score(expect, predict)) for expect, predict in zip(expected, predicted)]
    meteor_score_res = np.mean(meteor_score_sentences_list)
    return meteor_score_res