ML-KWS-for-MCU
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Keyword spotting on Arm Cortex-M Microcontrollers
Hi, I have been trying to reproduce the same DS-CNN architecture in Keras mode in Edge Impulse Studio. I implemented the exact same arch and try to give the system...
Hi, Could you share the commands/python calls used to generate the ds_cnn_weights.h file in \Deployment\Source\NN\DS_CNN? :) I am assuming one can use one of the pretrained models, either DS_CNN_L.pb/M/or S,...
Hi. I've tried to run, quantize and the compile the dnn model with 3 layers and 436 neurons for each layers. It is possible to launch the command: python train.py...
Faild to link kws_simple_test after compiling,The problem is described as follows: arm-none-eabi-cpp:fatal error:‘-c’ is not a valid option to the preprocessor compilation terminated.
$ mbed new kws_simple_test --mbedlib [mbed] Working path "E:\AI\KWS\Git\ML-KWS-for-MCU\Deployment" (program) [mbed] Creating new program "kws_simple_test" (git) [mbed] Adding library "mbed" from "https://mbed.org/users/mbed_official/code/mbed/builds" at branch/tag "tip" [mbed] Unpacking library build "65be27845400"...
Is there an update to work with tensorflow version 2, especially for train.py? Indeed, the most problematic line is `from tensorflow.contrib import slim as slim ` because there is no...
When I try to run my own audio recordings using `label_wav.py`, I always get random predictions. I trimmed the audio files to only contain the keyword and still receive false...
im getting this error. ``` (py37) C:\projects\audio\ML-KWS-for-MCU>python label_wav.py --wav yesno.wav --graph Pretrained_models/DNN/DNN_S.pb --labels Pretrained_models/labels.txt --how_many_labels 1 C:\Users\MasterRoot\Anaconda3\envs\py37\lib\site-packages\tensorflow\python\framework\dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated;...
my checkpoint path is absolute path but it is valueerror when i ran the freeze.py in the ML-KWS-for-MCU.How can i solve this problem?
Compare different models ,i find that the DS-CNN model train slower than other models on the same training set;but DS-CNN model predicted faster than the other models. Because of the...