In the next days I'm going to receive an audio dataset for a machine learning project at university. The files I'm going to receive are of 2 kinds: one that is the original entire audio audio sequence and the other that is composed of short sequences of the original file cut and put together in a single "summary" file (one summary for each original file). The problem is that I need to know from which point in time every subsequence was cut, but they cannot provide me with this information. Is there a program to deal with this problem?
Providing they are exact extracts of the audio files you could use python and numpy to load each audio sequence as a numeric array and then search the full audio files, also as a numeric array for the fragment.
Since all of your audio summary sequences are joined together in a single file you will need to find a window size that produces a unique fingerprint to locate in your large file, (I would suggest starting at about 5-10 seconds worth and scan the big file - if you get more than one match increase the sample size. Once you have a unique match you can carry on from that point in both files until they differ - that will give you your position in the full file and the duration of the first clip. You can then take a new fragment from the summary after the end of the match and repeat the process.