FAST HEARING · QUANTIZATION · TIMESTAMPS
faster-whisper
@SYSTRAN
Connect Whisper hearing to the real-time companion pipeline with less memory and faster inference.
faster-whisper optimizes the speed and memory usage of Whisper, making voice messages, call transcription and long audio processing more suitable for daily operations.
Project address (can be copied to AI):https://github.com/SYSTRAN/faster-whisper
PROJECT INTRO
Project introduction
faster-whisper uses CTranslate2 to run Whisper, supports GPU and CPU quantization, batch transcription, word-level timestamps and Silero VAD, and provides a calling method similar to common Python pipelines.
It is suitable for providing a more efficient auditory backend for partner voice messages, real-time calls, or long audio memory processing.
- Suitable for:A native speech system requiring high-throughput, low-memory Whisper transcription.
- Platform:Python, supports CPU and NVIDIA GPU.
- Usage:Install faster-whisper, load the model and select calculation accuracy and VAD settings.
- License:MIT。
COMMENTS & FEEDBACK
Comments and Feedback
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SOURCE & CREDIT
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