Discriminative analysis for image to sound mapping

This paper presents a comparison study of the existing methodologies for the conversion of images to sounds and determines the suitability and reliability of these techniques of data mapping. It also discusses enhancements that are needed to improve these mapping techniques. Many people have tried image-to-sound mapping or data-to-sound mapping and failed to prove the useful results and many people haven't followed the principles of psychoacoustics in implementing image to sound conversion methods. They failed to utilize the limitations of the human hearing system. The important bottleneck in this kind of experiments is that humans can't remember the normal sounds as compared to music. Most of the available tools have been tested on the participants and has been discovered that the technology available to convert data streams into sounds was not sufficient and needed an improvement.