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KWS Readme.md: inline image
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examples/example_kws_speech/README.md

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Module takes mono input 16bit PCM audio stream of 16kHz sample rate by frames of 15ms length (240 samples – stride size). FBANK Feature are calculated from 30ms long frame extracting 13 values from each frame.
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When input features sequence is long enough to perform complete NN Inference (features for 65 frames), module invokes MLI based NN implementation of the following architecture:
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[DSCNN_LSTM_NN](kws/dsconv_lstm_nn/DSCONV_LSTM_NN.png)
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![DSCNN_LSTM_NN](kws/dsconv_lstm_nn/DSCONV_LSTM_NN.png)
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The following table provides accuracy performance of trained model and it’s MLI based version for various bit depth of quantized data:
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