Search Results for "core-analyzer"

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.

Laravel Translation Manager is a package that adds a web-based UI and database-backed workflow for managing Laravel translation files. Instead of replacing Laravel’s built-in translation system, it imports your lang PHP/JSON files into a database so you can view, search, and edit keys and values from a browser. Once translations are updated, you can export them back to flat files so your app continues to use the standard Laravel translation loader. This workflow is especially helpful when...

...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.

Stanford Phrasal is a state-of-the-art statistical phrase-based machine translation system, written in Java. At its core, it provides much the same functionality as the core of Moses. Distinctive features include: providing an easy to use API for implementing new decoding model features, the ability to translating using phrases that include gaps (Galley et al. 2010), and conditional extraction of phrase-tables and lexical reordering models. Developed by The Natural Language Processing Group at Stanford University, a team of faculty, postdocs, programmers and students who work together on algorithms that allow computers to process and understand human languages. ...

PRDL is one of the core components within the ENDORSE project. The scope of the language is to encompass clauses from data protection legislation and enterprise privacy policies in order to e.g. derive data access decisions automatically based on the enterprise privacy policies (EPPs). There have been many initiatives for expressing privacy rules and legal restrictions into a computable way.