1. A method for performing acoustic dynamic classification of a breathing session using a processor coupled to a memory, said method comprising: capturing breathing sounds of a subject using a microphone; processing said breathing sounds to generate an audio respiratory signal; recognizing a plurality of breath cycles and a plurality of breath phases within each of said plurality of breath cycles from said audio respiratory signal; detecting characteristics regarding said plurality of breath cycles and said plurality of breath phases; and extracting and outputting metrics concerning a breath pattern quality of said subject using said characteristics wherein said metrics are selected from a group consisting of: respiratory rate; depth; tension; nasal wheeze; tracheal wheeze; pre-apnea; apnea; ramp; flow; variability; and inhale/exhale ratio; wherein said recognizing comprises: obtaining a first audio envelope by filtering an audio respiratory signal, wherein said obtaining comprises calculating a spectral centroid of each block of said audio respiratory signal and filtering said audio respiratory signal with a low pass filter tuned to a minimum value of said spectral centroid; classifying lobes of said first audio envelope into a plurality of classes; and defining said plurality of breath cycles and said plurality of breath phases using timestamps obtained from said classifying.