A system and method for determining users personality types, profiles, and infer the likely intent based on the users' musical taste and listening habits. The process involves identifying the listener's musical preferences and linking this to a predetermined scale within the psychological Big 5 that in turn links to a dictionary of descriptors that defines the personality type. This can be further fine tuned by knowing the persons age, gender, and many other lifestyle variables, as well as how a user may use the music.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: providing a database comprising digital song files; mathematically analyzing said digital song files, using a computerized device, said mathematically analyzing determining a numerical value for each of a plurality of selected quantifiable characteristics, each of said quantifiable characteristics comprising a physical parameter based on human perception; providing samples of songs selected from said database to a user; permitting said user to subjectively indicate likes and dislikes for each of said samples of said songs; determining a music taste profile for said user based on said likes and dislikes indicated by said user; linking said music taste profile for said user to a predetermined psychological scale; and identifying human psychological traits that are distinct from said music taste profile, based on said music taste profile to classify said user into a known psychological type scale. 2. The method according to claim 1, said mathematically analyzing said digital song files further comprising: compiling a song vector comprising a list of numerical values for each of said plurality of selected quantifiable characteristics for each said digital song file; and extracting a plurality of music descriptors for each song vector. 3. The method according to claim 2, said mathematically analyzing said digital song files further comprising: using fast Fourier Transform techniques to establish a plurality of sonic coefficients, said sonic coefficients being representative of said characteristics of said song. 4. The method according to claim 1, further comprising: choosing two dissimilar samples of songs from said database; enabling said user to listen to both of said two dissimilar samples of songs; receiving an indication of which of said two dissimilar samples of songs said user prefers; and choosing additional dissimilar samples of songs, as necessary, to establish a taste vector for said user comprising song characteristics that said user prefers. 5. The method according to claim 1, said predetermined psychological scale comprising: openness; conscientiousness; extraversion; agreeableness; and neuroticism. 6. The method according to claim 1, said identifying human psychological traits further comprising: identifying personality triggers from said music taste profile; linking said personality triggers to a dictionary of descriptors defining a personality type according to musical tastes; and producing a personal profile based on a determined personality type. 7. The method according to claim 1, further comprising: providing recommendations based on said music taste profile and said personality traits, said recommendations being related to one of music, films, television, and books. 8. The method according to claim 1, said method being performed using a real-time process based on dynamic interaction with said user. 9. A computer implemented method of determining psychological evaluation based on music preferences, said method comprising: providing a database comprising digital song files; mathematically analyzing said digital song files, using a computerized device, said mathematically analyzing determining a numerical value for each of a plurality of selected quantifiable characteristics, said quantifiable characteristics comprising physical parameters based on human perception; choosing samples of two songs from said database, using said computerized device; enabling a user to listen to both of said samples of two songs, using said computerized device; receiving an indication of which of said samples of two songs said user prefers, using said computerized device; choosing additional samples of songs, as necessary, to establish a taste vector for said user comprising song characteristics that said user prefers, using said computerized device; determining a music taste profile for said user based on likes and dislikes indicated by said user, using said computerized device; linking said music taste profile for said user to a predetermined psychological scale, using said computerized device; identifying human psychological traits that are distinct from said music taste profile, based on said music taste profile, using said computerized device; and classifying said user into a known psychological type scale, using said computerized device. 10. The computer implemented method according to claim 9, further comprising: providing recommendations to said user based on said music taste profile and said personality traits, using said computerized device, said recommendations being related to one of music, films, television, and books. 11. The computer implemented method according to claim 9, said mathematically analyzing said digital song files further comprising: compiling a song vector comprising a list of numerical values for each of said plurality of selected quantifiable characteristics for each said digital song file; and extracting a plurality of music descriptors for each song vector. 12. The computer implemented method according to claim 11, said mathematically analyzing said digital song files further comprising: using fast Fourier Transform techniques to establish a plurality of sonic coefficients, said sonic coefficients being representative of said characteristics of said song. 13. The computer implemented method according to claim 9, said identifying human psychological traits further comprising: identifying personality triggers from said music taste profile; linking said personality triggers to a dictionary of descriptors defining a personality type according to musical tastes; and producing a personal profile based on a determined personality type, said human psychological traits being based on said music taste profile. 14. The computer implemented method according to claim 9, said method being performed using a real-time process based on dynamic interaction with said user. 15. A system comprising: a digital database comprising digital song files; a processor operatively connected to said digital database; and a user interface operatively connected to said processor; said processor mathematically analyzing said digital song files and determining characteristic vectors for songs in said digital song files, said characteristic vectors comprising a numerical value for each of a plurality of selected quantifiable characteristics, each of said quantifiable characteristics comprising a physical parameter based on human perception said processor selecting samples of two songs from said database and enabling a user to listen to both of said samples of two songs using said user interface, said processor receiving an indication of which of said samples of two songs said user prefers, using said user interface, said processor selecting additional samples of songs, as necessary, to establish a taste vector for said user comprising song characteristics that said user prefers, said processor determining a music taste profile for said user based on said user's likes and dislikes, age, sex, and location said processor linking said music taste profile to a predetermined psychological scale, said processor identifying human psychological traits that are distinct from said music taste profile, based on said music taste profile and classifying said user into a known psychological type scale. 16. The system according to claim 15, further comprising: said processor providing recommendations to said user on said user interface, said recommendations being based on said music taste profile and said personality traits. 17. The system according to claim 16, said recommendations being related to one of music, films, television, books, leisure time interests, means of advertising, and otherwise communicating with consumers. 18. The system according to claim 15, said processor mathematically analyzing said digital song files further comprising: said processor compiling a song vector comprising a list of numerical values for each of said plurality of selected quantifiable characteristics for each said digital song file; and said processor extracting a plurality of music descriptors for each song vector. 19. The system according to claim 18, said mathematically analyzing said digital song files further comprising: said processor using fast Fourier Transform techniques to establish a plurality of sonic coefficients, said sonic coefficients being representative of said characteristics of said song. 20. The system according to claim 15, said processor identifying human psychological traits further comprising: said processor identifying personality triggers from said music taste profile; said processor linking said personality triggers to a dictionary of descriptors defining a personality type according to musical tastes; and said processor producing a personal profile based on a determined personality type, said human psychological traits being based on said music taste profile.