Extracting MFE features from audio samples
Edge Impulse relies on the impulse to craft all data processing tasks, including feature extraction and model inference. In this tutorial, we will see how to create an impulse to extract MFE features from our audio samples.
Getting ready
In Edge Impulse, an impulse is responsible for data processing and consists of the following two sequential computational blocks:
- Processing block: This is the preliminary step in any ML application, and it aims to prepare the data for the ML algorithm.
- Learning block: This is the block that implements the ML solution, which aims to learn patterns from the data provided by the processing block.
The processing block determines the ML effectiveness since the raw input data is often unsuitable for feeding the model directly. For example, the input signal could be noisy or have irrelevant and redundant information for training the model, just to name...
