Hardware Configuration and Performance Optimization Strategies
realtime-transcription-fastrtc provides a multi-level hardware optimization scheme:
- GPU acceleration: Full support for CUDA and MPS (Metal Performance Shaders), recommended for use with NVIDIA graphics cards.
- Model Selection: Five pre-trained models are provided from whisper-small (39M parameters) to whisper-large (1550M parameters)
- Performance Tuning: Support for tuning the batch_size parameter to balance latency and throughput
Specific recommendations for different hardware configurations:
- Higher-end devices: recommended whisper-large-v3-turbo model with batch_size set to 32
- Mid-range devices: whisper-medium model recommended, batch_size set to 8
- Low-volume devices: use whisper-tiny model with VAD turned off
The model warm-up mechanism at the first run effectively reduces the latency of subsequent recognitions.
This answer comes from the articleOpen source tool for real-time speech to textThe
May not be reproduced without permission:AI productivity tools " Hardware optimization of realtime-transcription-fastrtc ensures a smooth running experience.
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