Determine if two signals are the same?
Valuable results can be obtained using Mel Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW).

Divide the signal in multiple segments. I recommend to use an overlap of 50%. Compute the MFCCs for each frame, then you will obtain a vector of MFCCs for each frame. Finally you will have a matrix of [No of MFFCs, Number of frames], for each signal. To compare the similarity between sequences with different time length, compute the Euclidean distance between the two matrices. Also you can use the standardized Euclidean distance (check scipy.spatial.distance.cdist for Python).

cost_matrix = cdist(x, y, metric='euclidean')


Thus, you will obtain a cost matrix. Applying the DTW algorithm on this cost matrix, you will find the score which will tell you the similarity between the input signals. I recommend you to see how a different number of MFCCs affects the results and also take in consideration the length of the signals.

I recommend this link to read more details about MFCCs and there is a useful video tutorial about DTW. Also you can find many articles about DTW, it is a well known measure for the similarity between two time series.