OpenTranscribe is a self-hosted transcription platform that converts your audio and video library into searchable, speaker-labeled transcripts, then lets you summarize and chat with those recordings. Upload files up to 15 GB, record from the browser microphone, or paste a link from YouTube and a thousand other sites, and playlists queue up for batch processing automatically. WhisperX produces word-level timestamps in over 100 languages, while the diarization engine works out who spoke when, corrects turn boundaries, and recognizes the same voice again across different recordings. Speaker profiles accumulate a voice fingerprint, speaking-time analytics, and merged identities, so a regular guest is named correctly in every episode without relabeling. Point it at an LLM and recordings gain structured summaries with action items, suggested tags and collections, and a chat interface that answers questions about your transcripts with citations, grouped into projects that pin their source recordings and standing instructions. Leave the model unconfigured and transcription, diarization, full-text and semantic search, and redaction still run entirely on local models. Watch folders, S3 buckets, and network shares import new media on a schedule with three-layer deduplication and automatic stitching of split recordings, and everything exports as subtitles, Word or PDF documents with citeable numbered lines, or Markdown. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

ScribeCrate is a self-hosted speech-to-text API that turns recordings into transcripts, subtitles, and English translations on your own server. It speaks the OpenAI Whisper API fluently: point any compatible client at your server's address, swap in your API key, and uploads come back as text. Ask for plain text, JSON with timestamps, or ready-to-publish SRT and WebVTT subtitle files, and for long recordings the segments can stream back over SSE as they are decoded. Turn on speaker diarization and every segment is labeled with who is speaking, which makes interview and meeting transcripts readable at a glance. Choose the model that fits the job, from tiny for quick drafts to large-v3 for maximum accuracy, and run it on a modest CPU, a Raspberry Pi class ARM board, or an NVIDIA GPU. Almost any recording works: MP3, M4A, WAV, WebM, OGG, and FLAC are all accepted, and with models cached in advance the server keeps transcribing with no internet connection at all. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Speakr transforms audio recordings into organized, searchable, AI-enhanced notes with speaker recognition that identifies who said what across your entire recording library. The Python/Flask backend with Vue.js 3 and Tailwind CSS frontend deploys via Docker on port 8899, offering multiple transcription engines through auto-detected connectors: WhisperX for local processing with speaker diarization and voice embeddings, OpenAI Whisper and GPT-4o-transcribe, Mistral Voxtral for cloud diarization, AssemblyAI for multi-hour files, and any custom ASR webservice. Speaker voice profiles use embedding comparison to recognize individuals across different recordings automatically, while custom vocabulary biases the transcriber toward domain-specific jargon. The AI layer goes well beyond transcription: customizable summaries with per-recording, per-tag, and per-folder prompt templates; event extraction surfacing action items and calendar events; per-recording chat with streaming responses; and Inquire Mode for semantic search and natural-language queries across your entire library simultaneously. Smart tags execute custom AI prompts on transcripts for automatic categorization. The REST API with Swagger documentation supports signed webhooks integrating with n8n, Zapier, and Make. Auto-export pushes to Obsidian and Logseq, auto-processing watches directories, and the installable PWA provides mobile-first, offline-capable access with share-target support. 3,600+ stars since May 2025. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Subarr is the coordination, measurement, and quality layer for Whisper subtitle generation, sitting between Bazarr, Sonarr, Radarr, and subgen to decide what gets transcribed, in what order, and whether the result is any good. Its Coverage walk scans your whole library and scores every subtitle gap with a reason: no track, embedded-only, Bazarr-wanted, audio mislabeled, or low quality. Queue a file, a folder, or an entire series from the Library tab and watch it move through probing, transcribing, and write-back on the dashboard. The Review queue plays you the actual dialogue, picked out by voice-activity detection, so you can verify a subtitle really matches the audio language before it lands. It flags files whose default audio track is not the original language and swaps tracks in place, heading off the double-translation trap. A provider leaderboard records which subtitle sources actually deliver for your library, and the Tuning Lab lets you tune Whisper recipes against your own media. Rules and scheduled walks keep the work flowing, with Tautulli now-playing signals boosting whatever you are about to watch. Finished subtitles are written next to your media, and your Plex or Jellyfin library refreshes the moment one lands. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

The meeting ends and, instead of a raw transcript, you get minutes you can file: MeetDo is an open-source meeting-to-action system that hosts the meeting, captions it locally, and finishes the record for you. Start a browser meeting with video, screen sharing, and chat, and watch captions stream from a speech model running on the same infrastructure, so no audio is sent to a cloud note-taker. When the call ends, the transcript becomes structured minutes: summary, agenda flow, conclusions, and action items with owners, instead of a wall of raw text. Five meeting types, from management reviews and project weeklies to interviews and customer calls, shape the record, and custom templates export to DOCX or PDF with your original layout preserved. Domain vocabulary is corrected after recognition, so names, units, and industry terms survive transcription instead of turning into near-miss words. Past meetings stay searchable in a local history, and questions can be asked across them without anything leaving the machine. Editable transcripts let a human fix the record before it is filed, and the whole pipeline works offline after the first model download. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Vexa is the only Apache 2.0 meeting bot API that self-hosts the complete transcription pipeline, from bot dispatch to Whisper speech-to-text to knowledge agents, with zero audio leaving your infrastructure. A single POST /bots request sends a transcription bot into any Google Meet, Microsoft Teams, or Zoom call, where it captures audio, runs speaker-attributed transcription through faster-whisper or any OpenAI-compatible endpoint, and streams results to your application via real-time WebSocket with sub-second latency. The built-in agent framework watches live transcripts and your accumulated workspace context, answering mid-call questions grounded in your own meeting history and wiki. An MCP server connects Vexa to Claude, Cursor, and other compatible AI tools, turning every captured meeting into queryable context for external agents. The Terminal, a bundled Next.js web workbench, lets you send bots, watch live transcripts, manage users and API tokens, and chat with your meeting archive from a browser. Docker Compose brings the full stack up on one Linux host in five minutes; the Helm chart scales to thousands of users on Kubernetes with a Pod-per-bot architecture and built-in RBAC. Recordings persist in MinIO or any S3-compatible store, transcripts in Postgres, with Redis handling queues and scheduling. Deploy on RepoCloud for a dedicated VPS with full root SSH access and browser console. Apache 2.0 licensed.

Audio lectures become structured, Markdown-formatted notes in about a minute with ScribeWizard (also known as GroqNotes). Upload an MP3, WAV, or M4A file - or paste a YouTube link - and the app runs a three-stage pipeline on Groq's LPU inference hardware: Whisper Large v3 transcribes the audio, a larger Llama model drafts a comprehensive outline of the material, and a faster Llama model fills each section with detailed content. This scaffolded prompting strategy is the core idea: the strong model handles structure where quality matters most, the fast model handles volume, and Groq's 1200+ tokens-per-second inference keeps the whole process near real time. Output renders as clean Markdown with support for tables and code blocks, and finished notes download as text or PDF. Model selection is configurable - swap in other Groq-hosted open models like Mixtral or Gemma to trade speed against quality or work around rate limits. Built as a single Streamlit app by Benjamin Klieger at Groq, it needs only a Groq API key to run, making it one of the simplest self-hosted AI tools to operate.

Nojoin takes notes on your Meet, Teams, and Zoom calls without sending a bot into the meeting: it records from your browser and transcribes on your own server. Nothing extra joins the call and nothing announces itself to the room; you meet as usual, press record, and the browser captures the audio. Transcription runs locally with Whisper or Parakeet, so the audio never leaves your hardware, and speaker recognition matches voiceprints across calls, so a person you name once is labelled correctly in later meetings too. AI notes can come from an API provider, your existing Claude or ChatGPT subscription, or Ollama on the same machine for fully local processing. During the call, Meeting Edge suggests questions, flags points you may have missed, and explains unfamiliar terms in real time. Afterward, analytics measured from the audio report talk-time share, turn-taking, and overlapping speech. A built-in MCP server hands Claude or ChatGPT 32 tools over your library, 19 of them writable, so an assistant can search every meeting, correct a misheard line, turn action items into tasks, and reconcile attendees with your CRM. Google and Outlook calendars sync automatically, every meeting carries its own chat, and finished notes export to PDF, Word, or plain text. Stored credentials are encrypted with a key you control, and anonymous telemetry can be switched off entirely. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Subtitles are the one chore Sonarr and Radarr leave behind - Bazarr finishes the *arr media stack by automating them. It connects to both via their APIs and mirrors their libraries - it doesn't scan disk itself, it manages exactly what your *arr apps index. For every monitored episode and movie it checks existing internal and external subtitles against your language profiles, then hunts missing ones across dozens of providers - OpenSubtitles.com, Podnapisi, Addic7ed, Subscene, and many regional sources - covering 184 subtitle languages including forced/foreign-dialogue tracks. Matching is smarter than filename guessing: releases are compared by release group and source, some providers support exact file-hash matching, and every downloaded subtitle gets a percentage score. Set a minimum score per Sonarr/Radarr connection and Bazarr rejects weak matches; enable upgrades and it replaces previously downloaded subtitles when better ones surface. Out-of-sync files get fixed too - automatic subtitle synchronization realigns timing after download, triggered only below a configurable score threshold so good subs aren't touched. Per-show and per-movie language configuration, download history, manual on-demand search, and adaptive searching that throttles provider API calls round it out, all behind a clean Sonarr-style web UI written in Python. If your library serves multilingual viewers, this removes the last manual step.

When international movies and series arrive in a Radarr or Sonarr library without native-language captions, Lingarr automatically translates subtitle files across dozens of languages using local AI models or cloud translation engines. Connect your existing movie and television directories to scan media folders, identify missing target-language subtitles, and generate translated caption files alongside the original video streams. Administrators can configure an ordered chain of 13 translation backends, pairing a primary engine such as OpenAI, Anthropic, Gemini, DeepSeek, Mistral, xAI, or DeepL with automatic fallback to self-hosted LibreTranslate or local Ollama models whenever rate limits occur. Context-aware prompt templates inject preceding and following dialogue lines into each AI request so idioms, speaker tone, and timing remain natural across scene transitions, while batch translation mode processes multi-line blocks in a single call. From the web dashboard, users can browse indexed movies and episodes, trigger manual single-file or library-wide translations, and monitor active queues, progress percentages, and historical logs in real time. Scheduled background tasks and a documented REST API allow media servers to automate caption generation completely hands-free as new releases finish downloading. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

With OpenReader, any EPUB, PDF, Word document, Markdown file, or plain text book transforms into an interactive reading workspace paired with natural text-to-speech playback and multi-chapter audiobook export. Documents render natively in their original page layout rather than flattening into plain text, using layout-aware block detection and cross-page stitching so multi-column academic papers, technical manuals, and textbooks flow in the right reading order while skipping headers and footnotes. As narration plays, word-level forced alignment highlights each spoken word directly on the page in real time, and progressive background generation starts audio playback on the first segment while synthesizing upcoming pages ahead of your cursor. Readers can connect local speech engines such as Kokoro, KittenTTS, and Orpheus or cloud voice providers, select language-aware voices for multilingual books, adjust playback speed, and switch among thirteen light and dark reading themes. Cached audio segments persist across seeks and browser reloads, allowing the background worker to assemble complete M4B or MP3 audiobooks for offline listening on mobile devices while syncing reading progress, queues, and library imports across sessions. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Cap is an open-source screen recorder with a built-in sharing site, so the explanation you would have booked a call for becomes a link someone can watch whenever it suits them. Pick Instant Mode when speed matters: choose a screen, window, or area, add your camera and microphone, and the video uploads while you record, so the share link is ready the second you stop. Pick Studio Mode when polish matters: Cap records locally at up to 4K and 60 frames per second, keeps screen and camera as separate tracks, and opens an editor for trimming, backgrounds, zooms, captions, and export to MP4 or GIF. Whichever mode made it, a shared video lands on a page that plays in any browser, where viewers can leave comments and reactions. Owners can keep a video private or protect it with a password, and team workspaces keep a shared library organized. Share pages come from your own domain, and recordings live in the bundled object store or any S3-compatible bucket. Connect a transcription and AI provider to add transcripts, titles, summaries, and clickable chapters. Bug reports, product demos, onboarding walkthroughs, design reviews, and async standups all shrink to a short recording and a link. The desktop apps for macOS, Windows, and Linux connect to your server through a single Cap Server URL setting. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

You are halfway through a film when a scene begs to be shared, and Cliparr is the self-hosted clip maker that turns moments from your Plex, Jellyfin, or local video library into shareable clips without opening a full video editor. Connect a media server and Cliparr follows live playback sessions automatically, so the scene you are watching is already loaded when you decide to keep it. Local video files open directly in the browser without being uploaded anywhere first. Mark the range, fine tune the start and end, then crop the frame freely or to a fixed aspect ratio with mouse or touch controls, which makes vertical clips for phones as easy as widescreen ones. Exports run entirely in your browser as video, audio only files, or GIFs, so the server never turns into a render box and the clip lands on the device you are using. Source details, artwork, and clip timing travel inside supported containers, keeping the exported file labelled with where it came from. Captions are a first class step: write your own subtitles, import an existing file, style the text, and burn it into the picture before export. Editor keyboard shortcuts, access control, and reverse proxy support round out a tool that fits into an existing media setup instead of replacing it. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Muxarr cleans up your media library by stripping out the audio and subtitle tracks you will never use, so players stop offering twenty subtitle options and the wrong dub. Tell it which languages you actually watch and read, and it keeps those tracks while dropping commentary, foreign dubs, and redundant subtitles. Nothing is re-encoded: video and audio are copied as they are, so quality is identical and a large film finishes in about a minute instead of hours. Spare audio tracks alone often free ten to thirty percent of a file, which adds up quickly across a big library. Profiles apply different rules per directory, so anime, family films, and western shows can each keep different languages, with priority ordering, per-language limits, and fallback rules like English subtitles only when German ones are missing. Regional variants are understood, distinguishing Quebec French from France French or Latino from Castilian Spanish. When Sonarr or Radarr import something new, a webhook sends it straight to Muxarr, and original language detection makes sure a foreign film keeps its real soundtrack. Track names get cleaned of encoder tags, default and forced flags are fixed, and every output is validated before it replaces the original. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL-3.0 licensed.