OOONA Tools
Description
OOONA Tools offers professional online tools for subtitling and captioning, accessible from any computer at any time. The platform provides a simple and intuitive web interface for creating and editing captions and subtitles in any language. Features include frame-accurate text timing with an advanced timeline, video grid for precise caption positioning, audio waveform, and scene-change detection for accurate subtitle spotting. It supports import and export in various caption and subtitle formats, including TTML/DFXP, VTT, SCC, CAP, EBU-STL, SRT, IMSC1, PAC, 890, and more. Additionally, it supports generating image-based subtitles for DVD/Blu-ray/DCP authoring. Powerful Pro apps allow users to run automated QA scripts to check and fix files, as well as customize hotkeys and project settings.
Resource details
- Category path
- Media Tools
- Classification
- Not yet classified
OOONA Tools is cataloged in Media Tools. Its topics include subtitling, captioning, video editing, localization, and media production.
URL
Tags
Related resources
- SparseSync: Audio-Visual Synchronisation with Trainable SelectorsBMVC 2022 Spotlight paper and code for sparse-in-space-and-time audio-visual sync detection.
- whisper-subtitlesAccessibility-focused local subtitle generation using Whisper+OpenVINO, targeting hearing-impaired users across 99 languages.
- Eyevinn auto-subtitlesWhisper-based automatic subtitle generation tool that chunks large audio and outputs VTT/SRT/JSON while preserving sync.
- openrv-webWeb-based VFX viewer inspired by OpenRV, offering frame-accurate playback, CDL/LUT/curve grading, waveform/vectorscope/histogram, and A/B c…
- mkv2mp4Cross-platform Python GUI for batch MKV→MP4 conversion, with fast remux when streams are compatible and auto-transcode fallback plus SRT→mo…
- Evaluating Video Quality Metrics for Neural and Traditional Codecs (4K/UHD-1)Academic comparison of VMAF, AVQBits, and FasterVQA no-reference quality metrics on 4K content.
- Bitrate Ladder Construction via Transfer Learning and Spatio-Temporal FeaturesML-based bitrate ladder optimization achieving 94.1% complexity reduction at only 1.71% BD-rate cost using transfer learning.
- VMAF-torchPyTorch reimplementation of VMAF metric, GPU/gradient-friendly for use in learned codec optimization loops.
- CompressedVQA: Full/No-Reference VQA for Compressed UGC VideoICME 2021 grand challenge-winning full-reference and no-reference video quality models for compressed user-generated content.
- 2BiVQA: Double Bi-LSTM No-Reference Video Quality AssessmentNo-reference VQA model for UGC video using double Bi-LSTM, companion code to arXiv:2208.14774.