Search Results for "language processing"

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. ...

...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. This book is written in tex, and all source codes are open. This book is divided into four parts, each of which consists of several chapters. The order of the chapters refers to the time context of the development of machine translation technology, while taking into account the internal logic of the machine translation knowledge system.

...Its design prioritizes latency and robustness in noisy, far-field environments, enabling continuous transcription with low delay on mobile hardware. The engine manages audio front-end processing—such as noise suppression and voice activity detection—before feeding audio into compact, accurate acoustic and language models. Partial hypotheses stream as words are recognized, then stabilize with minimal jitter as confidence increases, which is crucial for usability. The code emphasizes efficient use of CPU and neural accelerators to balance battery life with responsiveness. ...

...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. 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.

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.