Cristinel Ababei / keyword_spotting_project Public
Target: Cortex-M4F 80MHz Clone this project

Test data

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Model variants
Test 'Unoptimized (float32)' model Test 'Quantized (int8)' model
Set the 'expected outcome' for each sample to the desired outcome to automatically score the impulse.

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Sample name Expected outcome Length Accuracy Result
marquette.24 marquette 600ms 100% 1 marquette
Show classification Show in data acquisition Show in feature explorer
marquette.29 marquette 600ms 100% 1 marquette
Show classification Show in data acquisition Show in feature explorer
marquette.25 marquette 600ms 0% 1 uncertain
Show classification Show in data acquisition Show in feature explorer
marquette.26 marquette 600ms 100% 1 marquette
Show classification Show in data acquisition Show in feature explorer
marquette.27 marquette 600ms 100% 1 marquette
Show classification Show in data acquisition Show in feature explorer
marquette.23 marquette 600ms 100% 1 marquette
Show classification Show in data acquisition Show in feature explorer
marquette.21 marquette 600ms 100% 1 marquette
Show classification Show in data acquisition Show in feature explorer
engineering.28 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
engineering.29 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
engineering.27 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
engineering.26 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
engineering.25 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
engineering.24 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
engineering.23 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
engineering.22 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
engineering.21 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
engineering.20 engineering 600ms 100% 1 engineering
Show classification Show in data acquisition Show in feature explorer
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Model testing output

Results

Model version:
Accuracy
94.12%

Confusion matrix

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Feature explorer

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