Research/Privacy Mode: Local Processing Without Compromise
productNovember 20258 min read

Privacy Mode: Local Processing Without Compromise

How we built an on-device speech recognition system that matches cloud performance.

Your Voice Stays With You

Privacy is not just a feature at Whisp—it's a fundamental principle. With our new Privacy Mode, all speech recognition happens entirely on your device. Your audio never leaves your computer, giving you complete control over your voice data.

The Technical Challenge

Building on-device speech recognition that matches cloud performance is extraordinarily difficult. Cloud-based systems have access to powerful GPUs, virtually unlimited memory, and large language models that would be impractical to run locally. Our challenge was to achieve comparable accuracy while respecting the constraints of consumer hardware.

Our Approach: Efficient Architecture Design

We developed a compact transformer architecture specifically optimized for on-device inference:

  • Knowledge Distillation: We trained our compact model to mimic the behavior of our larger cloud models, transferring knowledge while dramatically reducing size.
  • Quantization: We use 8-bit integer quantization for weights and activations, reducing memory footprint by 4x with minimal accuracy loss.
  • Sparse Attention: Our attention mechanisms use structured sparsity patterns that reduce computation by 60% while maintaining accuracy.
  • Neural Architecture Search: We used automated methods to discover optimal model architectures for different hardware constraints.

Hardware Acceleration

Privacy Mode leverages modern hardware acceleration features across platforms:

  • Apple Silicon: On Mac, we utilize the Neural Engine for efficient inference, achieving real-time performance with minimal battery impact.
  • Windows: We support DirectML for GPU acceleration across NVIDIA, AMD, and Intel graphics hardware.
  • Fallback: For systems without GPU acceleration, our optimized CPU kernels still provide responsive performance.

Accuracy Comparison

We're proud to report that Privacy Mode achieves 95% of our cloud model's accuracy on standard benchmarks. For most use cases, users will not notice any difference in transcription quality. The 5% gap primarily appears in edge cases like rare vocabulary or heavily accented speech.

Enabling Privacy Mode

Privacy Mode is available now in Whisp settings. Simply toggle "Privacy Mode" to enable fully local processing. Your personal dictionary and preferences remain synced across devices (encrypted end-to-end), but all audio processing happens locally.

Future Improvements

We're continuously improving our on-device models. Upcoming updates will include better support for specialized vocabulary, improved handling of multiple speakers, and even lower latency through further architectural optimizations.