the subtitle editor :)
13.4k
Stars
1.2k
Forks
224
Open issues
30
Contributors
AI Analysis
Subtitle Edit is a desktop application for editing, converting, and synchronizing subtitles with support for 200+ formats and video playback across Windows, macOS, and Linux. It serves professional subtitle editors, translators, and content creators who need offline, privacy-respecting subtitle manipulation with optional AI-assisted features like OCR and speech-to-text. General video editors and casual users benefit from it, but it is purpose-built for subtitle workflows rather than general m...
Inferred from signals mentioned in the README (tests, CI, type safety) — not a review of the actual code.
AI's overall editorial judgment — not an average of the bars above, can weigh other factors too.
Subtitle Edit: A mature, cross-platform subtitle editor with 12+ years of active development
Subtitle Edit is a feature-rich desktop application for creating, editing, converting, and synchronizing subtitle files. It targets content creators, translators, accessibility professionals, and home media enthusiasts who need precise control over subtitle timing, formatting, and format conversion. With 13,000+ stars, active daily commits, and broad format support, it occupies a strong position as the de facto open source subtitle editing tool. The offline-first, privacy-respecting design and cross-platform availability (Windows, macOS, Linux) make it practical for professional and hobbyist workflows alike.
Originally created in 2014 on GitHub but predates that as a long-running Windows application (development reportedly began around 2007). Migrated to cross-platform .NET over time, expanding from Windows-only to macOS and Linux support.
Growth appears steady and organic rather than viral — driven by word-of-mouth among subtitle communities, accessibility workers, and fansub groups. The shift to cross-platform availability likely broadened the user base. Consistent commits and releases sustain community trust. 75 stars in 7 days suggests ongoing low-level but persistent discovery.
Subtitle Edit is widely referenced in subtitle and accessibility communities, fansub forums, and media production workflows. It has been distributed via package managers and Flatpak, indicating real packaging and deployment effort. Exact download/usage statistics are not publicly available in the repository metadata, but community references and fork count (1,231) support non-trivial real-world usage.
Likely a desktop GUI application built on .NET (C#), using mpv and ffmpeg as external dependencies for video playback and media processing. Appears to follow a self-contained distribution model with bundled dependencies for each platform. The README suggests modular integration with optional third-party services for translation, STT, TTS, and OCR.
not documented in README
Exceptionally active — last push was 2026-06-22, less than 24 hours before the analysis date. Consistent long-term maintenance over 12+ years with no visible signs of abandonment. The README is detailed and up-to-date with platform-specific installation instructions, indicating ongoing care.
ADOPT IF: you need a mature, actively maintained desktop subtitle editor with broad format support, cross-platform availability, and offline-first privacy guarantees for professional or hobbyist use. AVOID IF: you need a fully automated, API-driven or headless subtitle pipeline — Subtitle Edit is a GUI application and not well-suited for server-side batch automation without workarounds. MONITOR IF: you rely on macOS or Linux and are concerned about polish parity with the Windows experience, as cross-platform support appears newer and may have rough edges not fully documented.
Independent dimensions
Mainstream potential
5/10
Technical importance
7/10
Adoption evidence
7/10
- Primary maintainer dependency: long-running projects led by a single core developer (niksedk) carry bus-factor risk if contributions remain concentrated.
- macOS distribution requires bypassing Gatekeeper due to lack of Apple signing, which may deter less technical users or organizational deployments.
- The .NET desktop GUI stack may face friction as platforms evolve, particularly on Linux where GUI toolkit consistency can be inconsistent.
- No documented test coverage makes it harder to assess regression risk as the feature set expands.
- Competition from AI-first captioning tools may reduce new user acquisition among users who prioritize automated workflows over manual editing.
Likely to remain the leading open source desktop subtitle editor for the foreseeable future, with gradual expansion of AI-assisted features (STT, translation integrations) while retaining its manual editing core.
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Languages
Information
- Language
- C#
- License
- MIT
- Last updated
- 6h ago
- Created
- 151mo ago
- Analyzed with
- anthropic/claude-haiku-4-5
Stars over time
Contributors over time
Top 100 contributors only — repos with more will plateau at 100.
Open issues
Logitech Options+ plugin for Subtitle Edit (MX Master, MX Keys, MX Creative Console)
Linux, US International with dead keys keyboard: dead keys do not work
Upload to brew
OCR result loses horizontal line centering visible in the source bitmap (.sup / PGS)
Improve shortcut categories
Open pull requests
Top contributors
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Aegisub is the traditional choice for advanced subtitle styling (ASS format), especially in fansub communities. Subtitle Edit covers more formats and is more actively maintained today; Aegisub development has been largely dormant. Different strengths: Aegisub excels at ASS typesetting, Subtitle Edit at broader format support and workflow tools.
ffsubsync is a CLI tool focused exclusively on auto-synchronizing subtitles to audio. It complements rather than competes with Subtitle Edit, which includes sync tools but also full editing capabilities. ffsubsync is more scriptable; Subtitle Edit is more complete for manual workflows.
Subliminal is a Python library and CLI for downloading subtitles from online providers. It solves a different problem (sourcing subtitles) rather than editing them. The two tools are complementary in most workflows.
VideoCaptioner targets AI-assisted subtitle generation from video using speech recognition and LLMs. It is newer, Python-based, and oriented toward automated captioning pipelines. Subtitle Edit has manual editing depth VideoCaptioner lacks, but VideoCaptioner may appeal to users wanting AI-first workflows.
Jubler is a Java-based subtitle editor with similar goals but significantly less active development and a smaller community. Subtitle Edit outpaces it in format support, maintenance cadence, and platform integration.