Search Results for "offline transcribe"
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Showing 8 open source projects for "offline transcribe"
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Handy STT
A free, open source, and extensible speech-to-text application
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 text field. ... -
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SpeechRecognition
Speech recognition module for Python
Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. -
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Buzz
Transcribe and translate audio offline on your personal computer
Buzz transcribes and translates audio to text offline using OpenAI's Whisper. Import audio and video files into Buzz and export them as TXT, SRT, or VTT files. Buzz supports Whisper, Whisper.cpp, Faster Whisper, Whisper-compatible models from the Hugging Face repository, and the OpenAI Whisper API. Get linux versions from: - https://flathub.org/apps/io.github.chidiwilliams.Buzz - https://snapcraft.io/buzz Home page of Buzz https://github.com/chidiwilliams/buzz Note for... -
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stt
Voice Recognition to Text Tool
stt is a standalone speech recognition tool that locally converts spoken content in audio or video files into textual formats without requiring internet access, giving users control over their data and reducing reliance on external APIs. It leverages open-source speech models such as Faster-Whisper to recognize and transcribe human speech into plain text, structured JSON objects, or subtitle files with time codes, making it suitable for both personal and professional transcription tasks. The... -
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5
Whishper
Transcribe any audio to text, translate and edit subtitles 100% locall
Open-source, local-first audio transcription and subtitling suite with a simple web UI. Thanks to open-source technologies, Whishper can run 100% offline. Your data never leaves your computer. Whishper allows you to translate your transcriptions to and from more than 60 languages thanks to Argos Translate and LibreTranslate. Download the transcriptions in many formats (json, txt, vtt, srt). Easily edit your subtitles right in the Web-UI. -
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Whisper Batch Transcriber
Unlimited, private and free Speech-To-Text program
## About: Automatically transcribe all of your voice recordings into clean, organized, neat text files. It's free, fully automated, unlimited, using state-of-the-art speech-to-text technology. Works 100% offline on your computer, privately and locally. ## Usecases: Convert speeches, podcasts, webinars, monologues, storytellings and other audio speech into a formatted .txt file. -
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The Hear
The Hear program is made for journalists.
To transcribe audio, the app uses the built-in speech recognition features of macOS. Turn your audio and video files into text You can change the font size by pressing the command and +/- keys. The font size is saved during further use. A folder "Hear" with text files is created on the desktop. The program is universal - arm64/x86_64 You can ask questions here https://sourceforge.net/p/the-hear/discussion -
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auto-subtitle
Automatically generate and overlay subtitles for any video
...The system can also translate subtitles into English, enabling multilingual accessibility for video content. Once the required models are downloaded, it can operate offline, making it practical for local workflows. Designed for simplicity, it provides a streamlined way to automate subtitle creation without manual transcription effort.
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