Search Results for "platform-tools"

Handy is a free, open-source, offline speech-to-text application built for privacy, accessibility, and extensibility. Developed using Tauri (Rust + React/TypeScript), it runs natively across Windows, macOS, and Linux while performing local speech recognition without sending any audio to cloud servers. Handy allows users to start transcription instantly using a configurable keyboard shortcut—press to record, release to transcribe—and automatically pastes the resulting text into any active...

RealtimeSTT is a Python-based realtime speech-to-text engine emphasizing low latency, wake-word detection, voice activity detection, and automatic speech segmentation. It provides asynchronous callbacks, nanosecond-precision timestamps, and CLI tools, suitable for building voice assistants, meeting transcribers, or live caption systems.

...A personal dictionary improves recognition of names, technical terms, and recurring phrases, while configurable global shortcuts support toggle and push-to-talk recording. Context-aware tools can use selected text, clipboard content, or visible screen text to improve the final output. The app is written in Swift, supports macOS 14.4 or later, can be installed through Homebrew, and is available under the GPLv3 license.

Free, open-source Opus Clip alternative for Windows. Turn long videos into platform-ready clips with local or cloud transcription, smart reframing, styled captions, and direct publishing. CLIPPING Auto: create 15s, 30s, 45s, 1m, or custom clips from the transcript Manual: click two words to set in/out points MCP: let an agent choose clips by word index with live preview Open the full GrepCut Studio editor from Clipper OVERLAYS Animated caption presets with live preview Adjust position, size, and words per line Add a logo or handle; control placement and opacity TRANSCRIPTION Run Parakeet or Whisper v3 Turbo locally, with optional MDX vocal isolation Or use your Groq/OpenRouter API key AUTOREFRAME Face and subject tracking for 9:16, 4:5, 1:1, and 16:9 Split view when two people won’t fit in one crop RENDER QUEUE Choose formats per clip Export at source quality, 1080p, or 720p PUBLISH Publish directly to TikTok and YouTube

Coqui STT is a fast, open-source, multi-platform, deep-learning toolkit for training and deploying speech-to-text models. Coqui STT is battle-tested in both production and research. Multiple possible transcripts, each with an associated confidence score. Experience the immediacy of script-to-performance. With Coqui text-to-speech, production times go from months to minutes. With Coqui, the post is a pleasure.

...----> Maintenance and improvement work has MOVED to https://cmusphinx.github.io/ Please go there for the most recent software and documentation. <---- CMUSphinx is a speaker-independent large vocabulary continuous speech recognizer released under BSD style license. It is also a collection of open source tools and resources that allows researchers and developers to build speech recognition systems.

It provides an interactive speech to text application that uses sphinx 4. With this you can use pre-recorded audio, record your own voice and convert incompatible audio/video to be compatible with sphinx 4. It currently supports U.S English by using hub4 acoustic and language model.

Yap MCP lets Claude, Cursor, VS Code, Windsurf and any MCP client transcribe local audio and video files (WAV, MP3, M4A, MP4, FLAC, OGG, Opus, WebM and more, any length) entirely on your computer with NVIDIA Parakeet TDT v3, the same speech engine as the Yap dictation app. 25 European languages detected automatically, optional timestamps, and a read-only search of your Yap dictation history. No upload, no API key, no account; the speech model (about 670 MB) downloads once and then it works offline. Tools: transcribe_audio, search_dictations, prepare_speech_model. Install: npx -y github:founden-bot/yap-mcp Claude Code: claude mcp add yap -- npx -y github:founden-bot/yap-mcp Source: https://github.com/founden-bot/yap-mcp (MIT license, Node.js 20+, macOS, Windows, Linux). The Yap team, O-mega Enterprise Inc.