How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
VizSeq is a Python toolkit for visual analysis on text generation tasks like machine translation, summarization, image captioning, speech translation and video description. It takes multi-modal sources, text references as well as text predictions as inputs, and analyzes them visually in Jupyter…
BLEURT is an evaluation metric for Natural Language Generation. It takes a pair of sentences as input, a reference and a candidate, and it returns a score that indicates to what extent the candidate is fluent and conveys the meaning of the reference. It is comparable to sentence-BLEU, BERTscore,…
Evaluation code for various unsupervised automated metrics for NLG (Natural Language Generation). It takes as input a hypothesis file, and one or more references files and outputs values of metrics. Rows across these files should correspond to the same example.
by NeuLab @ CMU LTI, and other contributors
The main features of neulab/compare-mt are: Evaluation.
Open-source alternatives to neulab/compare-mt include: facebookresearch/vizseq — VizSeq is a Python toolkit for visual analysis on text generation tasks like machine translation, summarization, image… google-research/bleurt — BLEURT is an evaluation metric for Natural Language Generation. It takes a pair of sentences as input, a reference and… maluuba/nlg-eval — Evaluation code for various unsupervised automated metrics for NLG (Natural Language Generation). It takes as input a…