Search Results for "translation"
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Showing 23 open source projects for "translation"
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MindNLP
Easy-to-use and high-performance NLP and LLM framework
MindNLP is a natural language processing library built on the MindSpore framework, providing tools and models for various NLP tasks. -
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Spark NLP
State of the Art Natural Language Processing
Experience the power of large language models like never before, unleashing the full potential of Natural Language Processing (NLP) with Spark NLP, the open source library that delivers scalable LLMs. The full code base is open under the Apache 2.0 license, including pre-trained models and pipelines. The only NLP library built natively on Apache Spark. The most widely used NLP library in the enterprise. Spark ML provides a set of machine learning applications that can be built using two main... -
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txtai
Build AI-powered semantic search applications
...Innovation is happening at a rapid pace, models can understand concepts in documents, audio, images and more. Machine-learning pipelines to run extractive question-answering, zero-shot labeling, transcription, translation, summarization and text extraction. Cloud-native architecture that scales out with container orchestration systems (e.g. Kubernetes). Applications range from similarity search to complex NLP-driven data extractions to generate structured databases. The following applications are powered by txtai. -
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torchtext
Data loaders and abstractions for text and NLP
We recommend Anaconda as a Python package management system. Please refer to pytorch.org for the details of PyTorch installation. LTS versions are distributed through a different channel than the other versioned releases. Alternatively, you might want to use the Moses tokenizer port in SacreMoses (split from NLTK). You have to install SacreMoses. To build torchtext from source, you need git, CMake and C++11 compiler such as g++. When building from source, make sure that you have the same C++... -
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NLG-Eval
Evaluation code for various unsupervised automated metrics
NLG-Eval is a toolkit for evaluating the quality of natural language generation (NLG) outputs using multiple automated metrics such as BLEU, METEOR, and ROUGE. -
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CSAw - NLP for low-resource languages
CSAw is an NLP framework for low-resource languages
CSAw is an NLP framework for low-resource languages with a focus on machine translation. The primary goal is to build language models automatically from bilingual text (e.g., front and back translations) using a deep transfer rule-based approach. The core of this strategy is the Concept Specification and Abstraction semantic representation which is specially designed with machine translation in mind. See the preprint article here: https://arxiv.org/abs/1807.02226 The current framework includes transduction algorithms (i.e., from text to semantic representation and back again) and some components needed for automatic language model building (lexical alignment and grammar rule generation). ... -
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MTBook
Machine Translation: Foundations and Models
This is a tutorial, the purpose is to introduce the basic knowledge and modeling methods of machine translation systematically, and on this basis, discuss some cutting-edge technologies of machine translation (formerly known as "Machine Translation: Statistical Modeling and Deep Learning") method"). Its content is compiled into a book, which can be used for the study of senior undergraduates and graduate students in computer and artificial intelligence related majors, and can also be used as reference material for researchers related to natural language processing, especially machine translation. -
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masmt
A frame work for Multi agent system development
MaSMT is a java based multi-agent system development framework, especially designed for development of English to Sinhala machine translation system. MaSMT also capable to develop any multi-agent based system through its architecture. Reference: B. Hettige, A. S. Karunananda, G. Rzevski, Multi-agent solution for managing complexity in English to Sinhala Machine Translation, International Journal of Design & Nature and Ecodynamics, Volume 11, Issue 2, 2016, 88 – 96. ... -
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nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
...It then covers TextCNN, recurrent networks, LSTM, bidirectional LSTM, sequence-to-sequence learning, and attention. Later examples implement the Transformer and BERT for translation, classification, and masked-token tasks. Paper links and Google Colab notebooks connect each implementation with its research background and an accessible runtime. -
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SRU
Training RNNs as Fast as CNNs
...SRU achieves 5--9x speed-up over cuDNN-optimized LSTM on classification and question answering datasets, and delivers stronger results than LSTM and convolutional models. We also obtain an average of 0.7 BLEU improvement over the Transformer model on the translation by incorporating SRU into the architecture. The experimental code and SRU++ implementation are available on the dev branch which will be merged into master later. -
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XLM (Cross-lingual Language Model)
PyTorch original implementation of Cross-lingual Language Model
XLM (Cross-lingual Language Model) is a family of multilingual pretraining methods that align representations across languages to enable strong zero-shot transfer. It popularized objectives like Masked Language Modeling (MLM) across many languages and Translation Language Modeling (TLM) that jointly trains on parallel sentence pairs to tighten cross-lingual alignment. Using a shared subword vocabulary, XLM learns language-agnostic features that work well for classification and sequence labeling tasks such as XNLI, NER, and POS without target-language supervision. The repository provides preprocessing pipelines, training code, and fine-tuning scripts so you can reproduce benchmark results or adapt models to your own multilingual corpora. ... -
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KSUCCA Corpus
A 50 million tokens corpus of Classical Arabic.
... • Arabic language teaching for both Arabs and non Arabs. • Artificial intelligence. • Natural language processing. • Information retrieval. • Question answering. • Machine translation. -
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TIES
A smart search engine for medical documents
TIES (Text Information Extraction System) is a clinical text search engine that uses Natural Language Processing techniques to extract medical concepts from free text clinical reports. It provides secure de-identified access to this information and has in built collaboration tools and honest broker functionality. It is licensed for academic use under the BSD license. For commercial use please contact Nexi at http://nexihub.com *** NOTICE: this software and forum are no longer... -
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Arabic Corpus
Text categorization, arabic language processing, language modeling
The Arabic Corpus {compiled by Dr. Mourad Abbas ( http://sites.google.com/site/mouradabbas9/corpora ) The corpus Khaleej-2004 contains 5690 documents. It is divided to 4 topics (categories). The corpus Watan-2004 contains 20291 documents organized in 6 topics (categories). Researchers who use these two corpora would mention the two main references: (1) For Watan-2004 corpus ---------------------- M. Abbas, K. Smaili, D. Berkani, (2011) Evaluation of Topic Identification Methods on... -
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AI learning
AiLearning, data analysis plus machine learning practice
...Our core members are certified as CSDN blog experts and short-book programmers as excellent authors. We have established ApacheCN, a non-profit document, and tutorial translation project. -
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Seq2seq Chatbot for Keras
This repository contains a new generative model of chatbot
...The data were collected from dialogues of English courses online. This trained model can be fine-tuned using a closed-domain dataset to real-world applications. The canonical seq2seq model became popular in neural machine translation, a task that has different prior probability distributions for the words belonging to the input and output sequences since the input and output utterances are written in different languages. The architecture presented here assumes the same prior distributions for input and output words. Therefore, it shares an embedding layer (Glove pre-trained word embedding) between the encoding and decoding processes through the adoption of a new model. -
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Phrasal
Statistical phrase-based machine translation system
...Our work ranges from basic research in computational linguistics to key applications in human language technology, and covers areas such as sentence understanding, automatic question answering, machine translation, syntactic parsing and tagging, sentiment analysis. -
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This project is devoted to the development of natural language processing tools and resources for the Lingala language, which is spoken by tens of millions of people in central Africa.
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AILOKS
A polylingual dictionary/ontology system
AILOKS is an acronym for Artificial Intelligence Linguistic Object Knowledge System. This dictionary is aimed to facilitate advanced NLP, translation engines and provide an effective dictionary interface to humans. This dictionary is Polylingual and should prove useful to language students, linguists and translators alike. It is part of a series of interrelated projects. -
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TextBlob
TextBlob is a Python library for processing textual data
Simple, Pythonic, text processing, Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more. TextBlob stands on the giant shoulders of NLTK and pattern, and plays nicely with both. Supports word inflection (pluralization and singularization) and lemmatization, as well as spelling correction. ... -
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LoonyBin is a workflow management system specifically geared toward the needs of computational research. It is currently used in Natural Language Processing and statistical machine translation. More at http://www.cs.cmu.edu/~jhclark/loonybin/.
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English-Khmer S. Machine Translation
English-Khmer Automatic Statistic Machine Translation (SMT)
Automatic Machine Translation from English to Khmer project is the first effort in Natural Language Processing field for translating English to Khmer (Cambodian) language. This project uses Domy CE, an open source SMT toolkit, for training parallel corpus and web technologies such as Python, Apache2, HTML, XML, and XSLT for developing web-based application. -
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This is a suite of several software agents to provide a complete architecture of lexical base as proposed in Didier Schwab's PhD. thesis. It will be used for automatic translation, information retrieval and other natural language processing tasks.
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