davabase/whisper_real_time
Whisper Real Time
Whisper Real-Time is a speech-to-text engine designed to convert continuous microphone input into written transcripts. It functions as a real-time audio processor that leverages the OpenAI Whisper model to generate immediate textual output from live spoken language.
The system utilizes a transformer-based architecture to map audio sequences to text tokens. It manages incoming data through a sliding-window buffering mechanism and a circular buffer, which ensures a steady stream of audio for the inference engine. To maintain accuracy during continuous processing, the software employs a stateful transcription context that retains a history of previous audio segments.
This tool supports a variety of applications, including live speech transcription, meeting note automation, real-time voice captioning, and voice command processing. The implementation uses an asynchronous inference pipeline to decouple audio capture from model processing, preventing the main execution loop from blocking during transcription.
Features
- Whisper-Based Engines - Provides a real-time transcription tool leveraging the transformer-based model for continuous audio processing.
- Speech Recognition Engines - Utilizes a transformer-based speech recognition engine to map audio sequences directly to text tokens.
- Real-Time Audio Transcribers - Converts continuous microphone input into written text in real time as the user speaks.
- Speech-to-Text Engines - Acts as a speech-to-text engine that translates spoken language into written transcripts using deep learning models.
- Speech Transcription Engines - Provides live speech transcription by converting continuous microphone input into written text using deep learning models.
- Rolling Context Windows - Maintains a rolling history of previous audio segments to provide linguistic context for accurate real-time decoding.
- Asynchronous Inference - Implements an asynchronous inference pipeline to decouple audio capture from model processing, preventing main-thread blocking.
- Meeting Automation & Transcription - Automates meeting note generation by transcribing live discussions into searchable text documents.
- Audio Stream Segmenters - Segments continuous microphone input into fixed-duration chunks using sliding-window buffering to maintain a steady stream for inference.
- Real-Time Video Captioning - Generates instant text overlays for live audio streams to improve accessibility and provide immediate written records.
- Voice Command Recognition - Captures live spoken input to trigger automated actions or control software interfaces through natural language recognition.
