Validate the FVP speech probabilities

Inspect the streaming decisions

The application sends one PROB line over the simulated UART for every 512-sample frame. It also merges consecutive speech frames into SEGMENT lines.

Inspect the first probability records and the detected speech segments:

    

        
        
grep -Eo 'PROB .*$' \
  silero-vad-work/fvp/fvp.log | head -n 10
grep -Eo 'SEGMENT .*$' \
  silero-vad-work/fvp/fvp.log

    

The output is similar to:

    

        
        PROB 0.000 0.211681 silence
PROB 0.032 0.211681 silence
...
PROB 0.224 0.995684 speech
...
SEGMENT 0.224 2.048 speech

        
    

Each PROB line contains the frame timestamp in seconds, the probability of speech, and the decision produced with a threshold of 0.55. Your probability values and speech segments depend on the validation audio.

The validation question is: Did the host and FVP label every frame the same way? In this run, both the host and the FVP found one speech segment from 0.224 to 2.048 seconds, with no decision mismatches.

Host and FVP produce the same speech decisions

Compare the host and FVP results

Compare the saved host reference with the probabilities in the FVP serial log:

    

        
        
source .venv/bin/activate
python3 examples/arm/silero_vad_example_ethos_u/runtime/compare_vad_probs.py \
  --expected silero-vad-work/export/expected_probs.bin \
  --actual-log silero-vad-work/fvp/fvp.log \
  --threshold 0.55 \
  --atol 0.25 \
  --mean-atol 0.02

    

The output is similar to:

    

        
        Compared 79 probability values
Max abs error: 0.156800 at frame 22
Mean abs error: 0.018459
Threshold mismatches at 0.550: 0

        
    

The comparison confirms that the host and FVP produced the same number of finite probabilities, and the numerical differences stay within tolerance. It also confirms that every frame has the same speech or silence decision.

What you’ve accomplished

You’ve completed an end-to-end streaming audio workflow for Arm Ethos-U. You exported Silero VAD with model-owned recurrent state and built a bare-metal Cortex-M85 application. You ran the application on the Corstone-320 FVP, and validated its speech decisions against a host reference.

You can now replace the example audio with another 16 kHz mono, 16-bit PCM WAV file, or use the runtime integration as a starting point for an Ethos-U85 device.