Evaluation code for various unsupervised automated metrics for Natural Language Generation.

Well tested & Multi-language evaluation framework for text summarization.

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

Image Caption metrics: Bleu、Cider、Meteor、Rouge、Spice

Code for paper title "Learning Semantic Sentence Embeddings using Pair-wise Discriminator" COLING-2018

A fast multithreaded C++ implementation of NLTK BLEU with Python wrapper.

Compute the price of a user hourly consommation from Enedis data export in the 3 regulated prices of EDF (tarif bleu)

Jointly Measuring Diversity and Quality in Text Generation Models

A python3 library for evaluating caption's BLEU, Meteor, CIDEr, SPICE，ROUGE_L，WMD score. Fork from https://github.com/ruotianluo/coco-caption

MAchine Translation Evaluation Online (MATEO)

Machine Translation (MT) Evaluation Scripts

Evaluation tools for image captioning. Including BLEU, ROUGE-L, CIDEr, METEOR, SPICE scores.

An effective and simple tool to calculate SacreBLEU, Token-BLEU, BLEU w/ compound splitting for fairseq

Implementation for paper BLEU: a Method for Automatic Evaluation of Machine Translation

A data driven query expansion approach for image caption, implemented in cpp

Automatic text metrics (BLEU, ROUGE, METEOR, +++)

Corpus level and sentence level BLEU calculation for machine translation

fnuv copia

Image caption generator is a task that involves computer vision and natural language processing concepts to recognize the context of an image and describe them in a natural language like English.

Evaluation of MT metrics on the WMT-21 Metrics data for English→Russian.