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Ok, so I'm trying to compare two different speech signals and I have come into a problem. Here goes:

I have split the signal into blocks, and I have computed the MFCC coefficients of each block. I then use a DTW algorithm to compare the (inputted) signal to the training signal.

Here is the data:

The training data is the MFCC values of a signal of someone saying "No". If I have the inputted signal of someone saying no the values then give:

13.9462, 55.8784, 38.3383, 29.9468, 32.7136, 24.8893, 34.0734, 24.3645, 39.329, 20.4847, 31.1939, 29.8841, 25.7655, 28.222, 23.1643, 33.4366, ....., ......

Where the max data for this dataset is: 97.4834

Here is the data for someone saying a different word:

28.6696, 65.8777, 44.2725, 31.6083, 42.6541, 38.4104, 26.6311, 34.9188, 37.2065, 25.2479, 41.5969, 54.2681, 37.0685, 26.2073, 33.9836, 38.7847, 28.3622, 67.8788, 74.9075, ....., ..... Where the max value in this dataset is: 97.5609

My guess (reading through the algorithm) is that the smallest difference should be the correct result. However, I do not know if it is possible to either:

1) Calculate the MAX value for each dataset and then see which value is smaller

2) Get the first variable and compare it.

Does anyone have any suggestions to how I would compare these kind of values?

Thank you

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