16. A mood detection machine to detect a speech-identifiable condition of a subject, comprising: a processor; a memory; a feature extraction module stored on the memory and adapted to cause the processor to: receive recorded speech data of the subject, the recorded speech data being transmitted by a communication device and recorded by an input of the communication device that receives the speech data for the subject while not receiving speech data for anyone else talking to the subject; perform, on the recorded speech data, a low-level feature extraction over a plurality of short-time segments to develop low-level feature data, and perform a segment-level feature extraction on the low-level feature data over a window of time to develop segment-level feature data, where the window of time comprises the plurality of short time segments contained therein, wherein the low-level feature extraction combined with the segment-level feature extraction masks out words contained in the recorded speech data such that the segment-level feature data is non-lexical data; and a decision module stored on the memory and adapted to cause the processor to: access a database of one or more classifiers, each classifier from among the classifiers corresponding to a different classification of the speech-identifiable condition; and determining the classification of the speech-identifiable condition of the subject from the segment-level feature data.
16. A mood detection machine to detect a speech-identifiable condition of a subject, comprising: a processor; a memory; a feature extraction module stored on the memory and adapted to cause the processor to: receive recorded speech data of the subject, the recorded speech data being transmitted by a communication device and recorded by an input of the communication device that receives the speech data for the subject while not receiving speech data for anyone else talking to the subject; perform, on the recorded speech data, a low-level feature extraction over a plurality of short-time segments to develop low-level feature data, and perform a segment-level feature extraction on the low-level feature data over a window of time to develop segment-level feature data, where the window of time comprises the plurality of short time segments contained therein, wherein the low-level feature extraction combined with the segment-level feature extraction masks out words contained in the recorded speech data such that the segment-level feature data is non-lexical data; and a decision module stored on the memory and adapted to cause the processor to: access a database of one or more classifiers, each classifier from among the classifiers corresponding to a different classification of the speech-identifiable condition; and determining the classification of the speech-identifiable condition of the subject from the segment-level feature data. 18. The mood detection machine of claim 16 , wherein the communication device is a cellular phone or a smart phone located remotely with respect to the mood detection machine, and wherein the communication device input is a microphone associated with the communication device.