I'm working on studying an endangered language and have the following problem: while I already have labeled exactly what the speakers I worked with have said at given timesteps on the word level and I know what possible lists of sounds/phones/letters can make up the word, I need a way to automatically detect the boundaries of the sounds with minimal data (maybe a few hours of recording).
To handle the case where a word may only be pronounced one way at first, I wonder if finding the difference or angle between MFCC vectors to create a function of MFCC change and then finding the max n points could work, but I'm not sure if there is a better way of doing this. I also worry about the fact that some boundaries may be less pronounced between sounds than others. I also don't know how to handle the case where a word may be pronounced with varying numbers of phones (eg. "texts" /t eh k s t s/ -> [t eh k s] or [t eh k s t s]).
Any help would be appreciated