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Whishper is a graphical user interface for transcribing audio and video files into text using the Whisper model. It serves as a speech-to-text tool and subtitle file generator that converts spoken content into editable text and timed subtitle formats.
The main features of pluja/whishper are: Graphical User Interfaces, Speech to Text Transcription, Audio and Video File Transcription, Transcription Exporters, Transcript Editors, Subtitle Segment Management, Language Translation Services, Speech Recognition Engines.
Projects with overlapping indexed features include: cmusphinx/pocketsphinx — PocketSphinx is an offline speech recognition engine that converts raw audio from files or live microphone streams… kedreamix/linly-dubbing — Linly-Dubbing is an automated video dubbing pipeline designed for multilingual video localization. It converts spoken… jianchang512/stt — This project is a hardware-accelerated transcription server and offline subtitle generator. It functions as a… elevenlabs/elevenlabs-python — This Python SDK provides a comprehensive toolkit for synthetic audio generation, voice cloning, and the development of… agermanidis/autosub — Autosub is a command-line media processor and automatic subtitle generator that converts audio streams from video and… linyqh/narratoai — NarratoAI is an automated video production pipeline that uses large language models to generate scripts, voiceovers,…
PocketSphinx is an offline speech recognition engine that converts raw audio from files or live microphone streams into written text without requiring a network connection. It functions as a speech-to-text library, a real-time transcription engine, and a voice command processor, capable of detecting and transcribing spoken commands from continuous audio streams with configurable acoustic and language models. The engine uses weighted finite-state transducers to represent acoustic, phonetic, and language models as a single search graph for efficient decoding. It employs fixed-point acoustic mod
Linly-Dubbing is an automated video dubbing pipeline designed for multilingual video localization. It converts spoken content in videos into another language by coordinating speech-to-text transcription, text translation, and text-to-speech synthesis. The system distinguishes itself through AI-driven lip synchronization and animation, which aligns facial expressions and mouth movements to the synthesized voiceover. It also utilizes audio source separation to isolate vocals from background music and noise, allowing for clean voice replacement while preserving original background audio. The br
This project is a hardware-accelerated transcription server and offline subtitle generator. It functions as a speech-to-text tool that converts audio and video files into plain text, JSON, and SRT subtitle formats using the Whisper model. The system operates as an OpenAI Audio API emulator, providing a local server that mimics a specific audio interface. This allows it to serve transcriptions to existing client configurations without requiring changes to the client software. The service utilizes GPU acceleration to increase voice recognition speed and includes utilities for hardware detectio
Autosub is a command-line media processor and automatic subtitle generator that converts audio streams from video and audio files into timed text overlays. It functions as an AI speech-to-text converter that uses OpenAI Whisper to generate synchronized subtitles. The tool includes a language translation pipeline to convert transcribed speech into target languages, enabling multilingual video captioning. It manages the process from audio-stream extraction to the serialization of final subtitle files for local storage. The system covers audio-to-text transcription, time-stamped text mapping, a