Search Results for "back"

...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.

...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 non-technical translators, product people, or content editors need to update language strings without touching the codebase. The tool supports scanning your codebase for new translation keys, organizing them by groups, and highlighting missing or untranslated entries. ...

STranslate is a lightweight, open-source machine translation front end that lets users translate text between languages using a variety of supported back-end translation engines or APIs, offering a simple GUI for quick translation tasks without needing to write code or use complex web UIs. The application is designed to be small, cross-platform, and flexible, giving users the ability to type or paste text and receive instant translations while optionally selecting the desired language pairs or switching between multiple service providers. ...

...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.