Hi Divya,
It is my understanding that you want to perform LPC for feature extraction for speech processing and emotion recognition. To perform the same, you can follow the below given steps:
- Load the speech signal using the ‘audioread’ function.
- Apply a pre-emphasis filter to amplify the high frequencies of the signal
- Frame the signal and divide it into overlapping frames to capture the temporal dynamics
- Window each obtained frame using a Hamming window to reduce spectral leakage
- Use the ‘lpc’ function to compute the LPC coefficients for each frame.
For more information regarding the process, you can refer the following documentations:
- lpc - https://www.mathworks.com/help/signal/ref/lpc.html
- Speech emotion recognition by feature extraction - https://github.com/AlinaBaber/Speech-Emotions-Recognition-by-feature-extraction-and-Deep-learning-MatLab
- LPC analysis and synthesis of speech - https://www.mathworks.com/help/dsp/ug/lpc-analysis-and-synthesis-of-speech.html
- Speech emotion recognition - https://www.mathworks.com/help/deeplearning/ug/sequential-feature-selection-for-speech-emotion-recognition.html
Hope this helps!
