This is a Windows application for automatic speech recognition that transcribes spoken audio from video files into timestamped SRT subtitle files. It serves as a subtitle generator and translation tool that converts media speech into synchronized text.
The main features of wxbool/video-srt-windows are: Whisper-Based Engines, Automatic Speech Recognition, Automated Video Transcribers, Bulk Media Transcribers, Subtitle Generators, Automated Subtitle Generators, SubRip Serialization, Subtitle Translation.
Open-source alternatives to wxbool/video-srt-windows include: buxuku/smartsub — SmartSub is a cross-platform desktop application for AI-driven video transcription and subtitle generation. It… weifeng2333/videocaptioner — VideoCaptioner is an automated tool designed to generate and embed time-synchronized subtitles into video files. By… agermanidis/autosub — Autosub is a command-line media processor and automatic subtitle generator that converts audio streams from video and… const-me/whisper — Whisper is a high-performance speech-to-text inference engine that uses graphics hardware shaders to accelerate the… ggerganov/whisper.cpp — whisper.cpp is a C++ implementation of the Whisper speech-to-text model, serving as a lightweight machine learning… m-bain/whisperx — WhisperX is an automated speech recognition toolkit designed to convert spoken audio into text while maintaining…
SmartSub is a cross-platform desktop application for AI-driven video transcription and subtitle generation. It converts audio and video files into text subtitles using local AI models and incorporates hardware acceleration to increase processing speed. The tool features a subtitle translator that leverages large language models, such as OpenAI and DeepSeek, to convert subtitles between different languages. It includes a visual editor for proofreading and polishing transcribed text, paired with a video preview for frame-accurate synchronization. The software supports batch processing of multi
VideoCaptioner is an automated tool designed to generate and embed time-synchronized subtitles into video files. By leveraging speech recognition models, the software converts spoken audio into text and calculates precise timestamps to ensure captions align with the original media. The project operates as a local-first inference pipeline, performing all transcription tasks on the host machine to maintain data privacy. It utilizes a transformer-based neural network for speech recognition and integrates a multimedia framework to handle the technical aspects of video processing and subtitle stre
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
Whisper is a high-performance speech-to-text inference engine that uses graphics hardware shaders to accelerate the transcription of spoken audio into written text. It implements a GPU-accelerated automatic speech recognition framework specifically designed to run Whisper models. The system focuses on high-speed processing for both recorded audio files and live microphone streams. It utilizes voice activity detection to analyze raw audio in real time, triggering the inference engine only when human speech is detected. The engine covers a broad range of capabilities including real-time audio