The printer sound has many aspects which define its quality because the printer has lots of components and its operation is very complicated. These sound qualities are related to the international competition in printer markets. Recordings inside anechoic chamber were analyzed and a large number of sounds were stimulated using digital signal processing technique. First subjective tests of the printer sound were conducted using semantic different method. By applying factor analysis to the subjective response, two important factors of sound quality were extracted. Second subjective tests were conducted to evaluate the quietness and the impulsiveness of the printer sounds. On the other hand, sound metrics are calculated applying psychoacoustic theories. In this paper, the nonlinear relation between subjective evaluation and sound metrics was identified using artificial neural network and the printer sound quality index was developed. Later, subjective sound quality evaluation will be estimated and evaluated using this index.