Signal feature identification
Your points 1 and 2 are not very different: 1) is the end results of a classification problem 2) is the feature that you give for classification. What you need is a good classifier (SVM, decision trees, hierarchical classifiers etc.) and a good set of features (pitch, formants etc. that you mentioned).
I'm am trying to identify phonemes in voices using a training database of known ones. 
I'm wondering if there is a way of identifying common features within my training sample and using that to classify a new one. 
It seems like there are two paths: 

Give the process raw/normalised data and it will return similar ones 
Extract certain metrics such as pitch, formants etc and compare to training set

My interest is the first!
Any recommendations on machine learning or regression methods/algorithms?