GSET MATLAB FILES
FOLDERS
- classes: contains data structures to organize data
- functions: contains functions to calculate signal information
- recordings: contains audio files from user authentication experiments, subfolders for individual users
- transmissions: contains chirp audio files transmitted by mobile device
- user_data: contains matlab variable files storing features for each user
CLASSES
- profile.m: structure for user data, holds user-influenced chirp signal and features extracted
FUNCTIONS
- func_chirp_gen.m: generates chirp signal based on parameters provided to it
- get_features: calculates time domain features when given user-influenced chirp signal
- get_freq_data: calculates frequency domain features such as mfcc, called by get_features
- mfcc.m: calculates mfcc variables
- trifbank.m: used by mfcc.m
- vec2frames.m: used by mfcc.m
MATLAB PROGRAMS <--- THIS IS THE REALLY IMPORTANT STUFF
- Step 1: create_chirp.m: choose what type of chirp signal to create, saves .wav file
- Step 2: cross_correlate.m: select audio file from audio folder and extract user-influenced signal from recording, creates profile ** Step 2 (Alternate): thresholding.m: cross_correlate may sometimes incorrectly calculate the user signal, thresholding is simpler method
- Step 3: feature_extraction.m: given user profile, calculate the features, saves user data into profile
- Step 4: learning.m: compiles all desired profiles into one data structure for classification learner app
- Step 4: gesture.m: compiles gesture data to test a different approach
CLASSIFICATION LEARNER APP <--- ALSO REALLY IMPORTANT
- In MATLAB, open the APPS tab at the top of the screen
- Click the Classification Learner icon (looks like bunch of red and blue dots)
- Start a new learning session by loading your desired workspace data (master_data created by learning.m)