Open Source Python Machine Translation Software
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Python Machine Translation Software
View 183 business solutionsBrowse free open source Python Machine Translation Software and projects below. Use the toggles on the left to filter open source Python Machine Translation Software by OS, license, language, programming language, and project status.
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Argos Translate
Open-source offline translation library written in Python
Argos Translate uses OpenNMT for translations and can be used as either a Python library, command-line, or GUI application. Argos Translate supports installing language model packages which are zip archives with a ".argosmodel" extension containing the data needed for translation. LibreTranslate is an API and web-app built on top of Argos Translate. Argos Translate also manages automatically pivoting through intermediate languages to translate between languages that don't have a direct translation between them installed. For example, if you have a es → en and en → fr translation installed you are able to translate from es → fr as if you had that translation installed. This allows for translating between a wide variety of languages at the cost of some loss of translation quality. -
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PDFMathTranslate
PDF scientific paper translation with preserved formats
PDFMathTranslate is a Python-based tool that uses AI translation to convert academic PDFs into bilingual (e.g. Chinese-English) documents while preserving formatting, including math notation. It supports OCR-enhanced content and offers CLI, GUI, Docker, and Zotero integration under AGPL v3. -
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pyVideoTrans
Translate the video from one language to another and embed dubbing
pyVideoTrans is an ambitious open-source multimedia processing project that assembles speech recognition, subtitle generation, AI translation, voice synthesis, and video assembly into a unified pipeline for converting videos from one language to another with embedded dubbing and captions. At its core it runs speech-to-text models to transcribe audio tracks, translates the resulting text into a target language using local or cloud-based translation engines, synthesizes new speech to match the translated subtitles, and then merges that speech back into the video, creating a fully localized media file. The tool supports both command-line and GUI modes, making it accessible to developers and creatives needing batch or automated processing. -
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bilingual_book_maker
Make bilingual epub books Using AI translate
bilingual_book_maker is an AI-assisted translation tool for creating bilingual and multilingual versions of books and text files. It is designed to process formats such as EPUB, TXT, SRT, and PDF, then generate translated output that helps readers compare the original text with the target language. The project supports multiple AI providers and models, including OpenAI-compatible models and other translation backends through LiteLLM-style integrations. It is especially useful for public domain books, language learning, subtitle translation, and personal reading workflows. Users can run it from Python scripts or install it as a command-line package for repeated translation tasks. The repository also includes documentation, test books, prompt templates, and configuration options for customizing how translations are generated. -
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Translation Agent
Agentic translation using reflection workflow
Translation Agent is a Python demonstration of an agentic translation workflow that uses reflection to improve machine translation quality. Instead of asking a language model for a single direct translation, it first generates a translation, then asks the model to critique it, and finally uses that critique to produce a stronger version. This structure makes the system more steerable than a traditional translation pipeline. Users can adjust prompts to control tone, formality, terminology, idiom handling, and regional language choices. The project includes example scripts and a simple Python interface for translating between source and target languages. It is useful for researchers, developers, and localization teams exploring how LLM-based workflows can produce better, more customizable translations. -
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Violin
Open-source Video Translation Skill
Violin is an open-source video translation and dubbing tool that turns existing videos into localized versions with translated voice-over and optional subtitles. It transcribes the original speech, translates the text, generates natural-sounding speech in the target language, and remuxes the new audio back into the video. The project is designed to keep the generated speech aligned with the original timing so the final result feels closer to a real dubbed video. It can be used from the command line, through a FastAPI web app, or as a Claude Code skill. Violin supports multilingual workflows and is useful for creators, educators, localization teams, and developers building automated video translation pipelines. It is especially practical for turning lectures, tutorials, interviews, demos, and social videos into accessible content for wider audiences. -
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LingoGeek
Free offline document translator for Windows - Word, PDF, subtitles
LingoGeek translates whole documents on your own machine. Word, PDF, SRT and VTT subtitles, Markdown and plain text, with no character limit. Most translation tools want pasted text, or cap you at one document a month. LingoGeek takes the file itself and has no cap at all, because nothing is uploaded. Headings, lists, tables, headers and footers keep their place in a Word document. Subtitle timings and cue numbers are copied through exactly, so only the spoken lines change. Your original is never touched. The translation is written as a new file beside it. Drop in a folder full and they go through one after another, block by block. Language packs are downloaded once and then it works offline. No account, no adverts, no telemetry. Open source under GPL-3.0. Windows 10 or 11, 64 bit. -
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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 Arabic Corpora,JOURNAL OF DIGITAL INFORMATION MANAGEMENT,vol. 9, N. 5, pp.185-192. 2) For Khaleej-2004 corpus --------------------------------- M. Abbas, K. Smaili (2005) Comparison of Topic Identification Methods for Arabic Language, RANLP05 : Recent Advances in Natural Language Processing ,pp. 14-17, 21-23 september 2005, Borovets, Bulgary. More useful references to check: ------------------------------------------- https://sites.google.com/site/mouradabbas9/corpora -
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Traductor de Pantalla: Inglés-Español
Traduce al español textos en inglés de tu pantalla: juegos y videos
Traductor gratuito para Windows que traduce del inglés al español cualquier texto de tu pantalla. Marcas una región con el mouse (o Ctrl+Alt+T) y en segundos la traducción aparece encima del original, en el mismo lugar y con los mismos colores: sin copiar, pegar ni cambiar de ventana. Usa OCR, así que traduce aunque el texto no se pueda copiar: juegos sin versión en español (diálogos, misiones, menús), videos con subtítulos en inglés, programas, mensajes de error, páginas web, PDF, imágenes, capturas y chats. Lee letra chica, tipografías decorativas y texto sobre imágenes. El reconocimiento se hace en tu PC: a internet solo sale el texto, nunca la imagen de tu pantalla. Gratis, sin cuentas ni suscripciones. Instalador en español, sin permisos de administrador. Requiere Windows 10/11 de 64 bits e internet. Ideal para gamers y estudiantes: una alternativa simple a los traductores de imágenes, directamente sobre tu escritorio. -
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CompE Toolkit
Data Type Converter
CompE Toolkit allows the user to seamlessly convert between binary, decimal, hexadecimal, and 32-bit floating point representation. It uses a simple, user-friendly interface designed for maximum efficiency and minimal clutter. -
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CycleGAN and pix2pix in PyTorch
Image-to-Image Translation in PyTorch
CycleGAN and pix2pix in PyTorch repository is a PyTorch implementation of two influential image-to-image translation frameworks: CycleGAN (for unpaired translation) and pix2pix (for paired translation). This repo gives developers and researchers a convenient, modern (PyTorch-based) platform to train and test these methods — supporting both paired datasets (input to output) and unpaired datasets (domain-to-domain) with minimal changes. The code supports standard training and inference pipelines, and as of recent updates, compatibility with the latest Python and PyTorch versions (e.g. Python 3.11, PyTorch 2.4) as well as support for distributed/multi-GPU training for scalable workflows. Because of its flexibility, users can apply it to many tasks: e.g. style transfer between domains (e.g. season changes, art-to-photo, etc.), mapping sketches/edges to real images, image colorization, day-to-night, photo enhancement, and more. -
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Pootle Django
Online translation tool
Pootle is written in Python using the Django framework and therefore can be installed on any web server that supports serving WSGI applications. Key localization file formats are supported, including Gettext PO, XLIFF, Java .properties, PHP arrays and many more supported by the Translate Toolkit. Ensures the best quality localizations by automatically detecting common errors made by translators. Integrates user suggestions, terminology, Translation Memory, Machine Translation, and more. A number of translation projects for a number of languages can be hosted on Pootle. Teams can manage their files, permissions, projects, and translate on-line. Files can be downloaded for offline translation. Delegate to your translators and allow them to commit directly to your version control systems. Pootle can easily be adapted and integrated into your existing web look and feel. -
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Self‑Healing Localization
Self‑Healing Localization is a lightweight Python library.
Self-Healing Localization Layer (SHL) is a Python localization engine that automatically creates, synchronizes, and maintains language files throughout the lifetime of your application. -
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A free Spanish - English Translator for Linux. It will translate a phrase (via internet) or single word (built-in dictionary.) Has capability to learn new words and is smart enough to find plural and feminine words. Written using Python/GTK under GPL
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UnsupervisedMT
Phrase-Based & Neural Unsupervised Machine Translation
Unsupervised Machine Translation is a research repository that implements both phrase-based SMT and neural MT approaches for translation without parallel corpora. The neural component supports multiple architectures—seq2seq, biLSTM with attention, and Transformer—and allows extensive parameter sharing across languages to improve data efficiency. Training relies on denoising auto-encoding and back-translation, with on-the-fly, multithreaded generation of synthetic parallel data to continually refresh supervision signals. The project also provides scripts to fetch and preprocess monolingual data, learn BPE codes, and train cross-lingual embeddings that bootstrap unsupervised alignment between languages. Beyond the core EMNLP 2018 setup, the codebase exposes additional, optional capabilities such as multi-language training, language model pretraining with shared parameters, and adversarial training. -
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dadosSemiotica
Collecter and manager of semiotica annalisis data
This program is a web application to collect and organize data of text analysis. It works with sets of texts and the analysis are done on portions of the length of a sentence. One of the preprocessing modules is based on CoGroo (A LibreOffice & OpenOffice.org Portuguese Grammar Checker). -
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t2t-pipe
automatic alignment pipeline for parallel treebanks
The *Tree-to-Tree (t2t) Alignment Pipe* is a collection of python scripts, co-ordinating the process of automatic alignment of parallel treebanks from plain text files with a single call from a unix command line. Supported Languages: DE, FR, EN
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