Determine the correct number of audio samples to feed into the coder.MFCCFeatureSet object (256). To calculate the length of each audio sample in an audio chunk (500 ms) using the number of samples in each frame (850). The number of audio chunks required for each file is determined by the number of audio files embedded on the disk. For example, the file that includes the first audio chunk is called \"01_01.m4a\". The time taken to calculate the audio chunks is determined using the calculateTimeTaken on the first file \"01_01.m4a\".
The generateIndexFeatures function receives audio data captured in a single frame. It determines the total number of speech commands (Categories) for the audio data captured in a single frame based on the index of each subarray segment. The index features are used by the node.batchPredict function. The batchPredict function takes 38 chunked audio samples captured in a single frame as input and generates the predicted1 sample as the output. Chunked features are used for the daisy chain communication between Raspberry Pi, the bluetooth module, and MATLAB by connecting the bluetooth module to the potentiometer.
The Feature Extraction function extracts features from audio data using a modified version of the ExtractFirstThreeMel-Filter feature extraction algorithm. The Frequency discretization step is removed and the duration for each window is reduced. The processing scale step is used to reduce the duration of the spectrogram to 1 second. The modification is necessary to process audio data that comes with a different sampling rate (16 kHz) for the network. Feature extraction is handled by the generateFirstThreeMelFeatures function.
Use the generated waveform to calculate mel-frequency cepstral coefficients (MFCCs) for the audio samples in frames with the generateMFCCFeatures function. Frame length is 50 ms. Calculate the total number of coefficients per frame. The coder.loadMFCCFeatures function loads the coder.MFCCFeatureSet object and the coder.MBFeature classes generated previously. On Raspberry Pi, you can visualize the change in the battery voltage over time with a one second interval. 7211a4ac4a