bleu-score 开源项目推荐（138 个）

Maluuba /nlg-eval

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

dabasajay /Image-Caption-Generator

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

anuragmishracse /caption_generator

A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.

gcunhase /NLPMetrics

Python code for various NLP metrics

MiteshPuthran /Image-Caption-Generator

The LSTM model generates captions for the input images after extracting features from pre-trained VGG-16 model. (Computer Vision, NLP, Deep Learning, Python)

Smoothex /BabyGPT

A basic AI chat using the OpenAI API and its GPT-3 models

golsun /NLP-tools

Useful python NLP tools (evaluation, GUI interface, tokenization)

AmirhosseinHonardoust /Image-Captioning-CNN-LSTM

An end-to-end image captioning project using a CNN encoder (ResNet-50) and LSTM decoder in PyTorch. Includes vocabulary building, preprocessing, training with BLEU evaluation, and inference. Generates natural language captions for images with saved metrics, model checkpoints, and visualization outputs.

desilinguist /ibleu

A visual and interactive scoring environment for machine translation systems.

tanjeffreyz /attention-is-all-you-need

PyTorch implementation of "Attention Is All You Need" by Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin

iranailab /eval_mt

To evaluate machine translation, they use several methods, some of which we fully implemented

shenxiangzhuang /bleuscore

BLEU Score in Rust

metalaman /Scripts-for-extractive-summarization

Scripts for an upcoming blog "Extractive vs. Abstractive Summarization" for RaRe Technologies.

bangoc123 /BLEU

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

himanshurawat443 /Abstractive-Text-Summarization-using-seq-2-seq-RNN-s

Abstractive text summarization done with the help of LSTMs using encoder-decoder model which was able to achieve accuracy of 77.27% on training set and cumulative BLEU-4 score of 0.8800 on test set.

su-mana-s /Semantic-Communication

Semantic Message Extraction for Text Based Data With Deep Neural Nets

LaurentVeyssier /Image-Captioning-Project-with-full-Encoder-Decoder-model

Generate caption on images using CNN Encoder- LSTM Decoder structure

Glareone /AI-RAG-In-Depth

Structured approach in AI and ML. Fundamentals and Advanced topics. RAG, Scoring & Profiling, LangChain & LangGraph, Certified Azure AI Engineer materials.

fooSynaptic /NLP-utils

Machine learning tools for NLP programming.

longday1102 /NMT-with-Seq2Seq

⚡ Seq2Seq model combines Attention mechanism