MJRoBot (Marcelo Rovai) / XIAO-ESP32S3-KWS Public
Target: Espressif ESP-EYE (ESP32 240MHz) Clone this project
Experiments EON Tuner
The EON Tuner helps you quickly run hyper-parameter sweeps that explore different pre-processing + model architectures optimized for your defined objectives. Clone this project to use the EON Tuner.

Target

No name set

Espressif ESP-EYE (ESP32 240MHz)

100 ms

4096 kB

4096 kB

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General

F1-score

Precision

Recall

90%
mfe-conv1d-afb
PERFORMANCE
LATENCY
265 ms of 100 ms
Exceeds target by 165 ms
RAM
20 kB of 4096 kB
ROM
66 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 90%

Type Filters Kernel Rate
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
dropout - - 0.5

5/22/2023, 7:14:09 PM

90%
mfe-conv1d-dae
PERFORMANCE
LATENCY
263 ms of 100 ms
Exceeds target by 163 ms
RAM
20 kB of 4096 kB
ROM
66 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 90%

Type Filters Kernel Rate
Data augmentation
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
dropout - - 0.25

5/22/2023, 7:14:58 PM

90%
mfe-conv1d-681
PERFORMANCE
LATENCY
167 ms of 100 ms
Exceeds target by 67 ms
RAM
13 kB of 4096 kB
ROM
30 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 90%

Type Filters Kernel Rate
conv1d 16 3 -
conv1d 32 3 -
dropout - - 0.5

5/22/2023, 7:19:29 PM

90%
mfcc-conv1d-3bd
PERFORMANCE
LATENCY
288 ms of 100 ms
Exceeds target by 188 ms
RAM
15 kB of 4096 kB
ROM
36 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 90%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.5

5/22/2023, 7:15:42 PM

90%
mfe-conv1d-59a
PERFORMANCE
LATENCY
168 ms of 100 ms
Exceeds target by 68 ms
RAM
15 kB of 4096 kB
ROM
38 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 90%

Type Filters Kernel Rate
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.25

5/22/2023, 7:06:47 PM

89%
mfe-conv1d-01a
PERFORMANCE
LATENCY
174 ms of 100 ms
Exceeds target by 74 ms
RAM
15 kB of 4096 kB
ROM
38 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 89%

Type Filters Kernel Rate
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.25

5/22/2023, 7:12:35 PM

89%
mfe-conv1d-832
PERFORMANCE
LATENCY
163 ms of 100 ms
Exceeds target by 63 ms
RAM
14 kB of 4096 kB
ROM
30 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 89%

Type Filters Kernel Rate
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
dropout - - 0.5

5/22/2023, 6:53:26 PM

89%
mfe-conv1d-82d
PERFORMANCE
LATENCY
168 ms of 100 ms
Exceeds target by 68 ms
RAM
15 kB of 4096 kB
ROM
38 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 89%

Type Filters Kernel Rate
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.5

5/22/2023, 7:09:37 PM

89%
mfe-conv2d-71c
PERFORMANCE
LATENCY
147 ms of 100 ms
Exceeds target by 47 ms
RAM
18 kB of 4096 kB
ROM
33 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.05 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 89%

Type Filters Kernel Rate
conv2d 8 3 -
conv2d 16 3 -
conv2d 32 3 -
dropout - - 0.5

5/22/2023, 7:19:03 PM

88%
mfe-conv1d-6c6
PERFORMANCE
LATENCY
229 ms of 100 ms
Exceeds target by 129 ms
RAM
17 kB of 4096 kB
ROM
30 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.05 | 0.025 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 88%

Type Filters Kernel Rate
Data augmentation
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
dropout - - 0.25

5/22/2023, 7:04:51 PM

88%
mfe-conv1d-f0f
PERFORMANCE
LATENCY
178 ms of 100 ms
Exceeds target by 78 ms
RAM
14 kB of 4096 kB
ROM
38 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 88%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.25

5/22/2023, 7:20:57 PM

88%
mfe-conv1d-afd
PERFORMANCE
LATENCY
160 ms of 100 ms
Exceeds target by 60 ms
RAM
13 kB of 4096 kB
ROM
27 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 88%

Type Filters Kernel Rate
conv1d 8 3 -
conv1d 16 3 -
dropout - - 0.25

5/22/2023, 7:10:13 PM

88%
mfe-conv1d-9bf
PERFORMANCE
LATENCY
172 ms of 100 ms
Exceeds target by 72 ms
RAM
14 kB of 4096 kB
ROM
38 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFE

0.032 | 0.032 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 88%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.5

5/22/2023, 7:06:13 PM

87%
mfcc-conv2d-795
PERFORMANCE
LATENCY
208 ms of 100 ms
Exceeds target by 108 ms
RAM
15 kB of 4096 kB
ROM
33 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.05 | 0.05 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 87%

Type Filters Kernel Rate
Data augmentation
conv2d 8 3 -
conv2d 16 3 -
conv2d 32 3 -
dropout - - 0.5

5/22/2023, 7:15:04 PM

87%
mfcc-conv1d-b70
PERFORMANCE
LATENCY
444 ms of 100 ms
Exceeds target by 344 ms
RAM
18 kB of 4096 kB
ROM
27 kB of 4096 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

MFCC

0.05 | 0.025 | 40

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 87%

Type Filters Kernel Rate
conv1d 8 3 -
conv1d 16 3 -
dropout - - 0.5

5/22/2023, 6:53:35 PM

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