The growing popularity of neural machine translation (NMT) and LLMs represented by ChatGPT underscores the need for a deeper understanding of their distinct characteristics and relationships. Such understanding is crucial for language professionals and researchers to make informed decisions and tactful use...
Irrespective of translation technology, the highest quality translations are always produced by customizing machine translation for a purpose and domain. As with all machine learning technologies, the right data will deliver better translation quality results. Language Studio includes the tools and ...
nmt g3doc scripts standard_hparams testdata utils .gitignore __init__.py attention_model.py gnmt_model.py inference.py inference_test.py model.py model_helper.py model_test.py nmt.py nmt_test.py train.py CONTRIBUTING.md LICENSE README.md ...
@inproceedings{wieting-17-backtrans, author = {John Wieting, Jonathan Mallinson, and Kevin Gimpel}, title = {Learning Paraphrastic Sentence Embeddings from Back-Translated Bitext}, booktitle = {Proceedings of Empirical Methods in Natural Language Processing}, year = {2017} }...
- Conference on Empirical Methods in Natural Language Processing 被引量: 23发表: 2017年 Dynamic Tuning and Weighting of Meta-learning for NMT Domain Adaptation Neural machine translation (NMT) systems fall short when training data is insufficient. For low-resource domain adaptation, meta-learning ...
具体描述这一过程如下:首先L1 decoder和L2 decoder分别为两个语言的语料库的Language Modeling(语言模型)。 左边的shared encoder是两个语料库公用的encoder,并且它的嵌入是fixed cross-lingual embedding(交叉语言的vocabulary)。 回译的过程如下: L1 sentence→shared encoder(L1)→L2 decoder→predict L2 sentence ...
Garbage Collection Algorithms for Java-Based Prolog Engines Implementing a Prolog Runtime System in a language like Java, which provides its own automated memory management and safety features (like built-in index c... Q Zhou,P Tarau - Springer Berlin Heidelberg 被引量: 15发表: 2003年 The di...
facebook开源官宣:https://ai.facebook.com/blog/ccmatrix-a-billion-scale-bitext-data-set-for-training-translation-models/ CCMatrix论文:https://arxiv.org/abs/1911.04944 CCMatrix开源链接:https://github.com/facebookresearch/LASER/tree/master/tasks/CCMatrix...
Dual-learning mechanism不仅适用于机器翻译场景,还适用于一下两个场景: 1、现实场景下很多任务都可以看做是一个对偶任务,比如语音到文本vs文本到语音,问答vs答案生成(问题到答案vs答案到问题),搜索(query到document)vs关键词抽取(抽取关键词/query for document)(query到文档vs文档到query)等,都可以基于对偶的学习机...
Joint Learning 该模型有两个解码器,即first-pass解码器和second-pass解码器,它们各自可以独立地学习参数以使负对数可能性最小。直观地说,这两个解码器是关联的,两者的性能都可以通过联合学习技术来提高。如前所述,使用一个奖励教师来奖励产生话语连贯性文本的模型。根据模型架构,有两种方法可以用来奖励学习策略的模型...