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when people are attaching or interesting in something, usually they are trying to interact with it frequently. Music is attached to people since the day of they were born. When music repository grows, people faced lots of challenges such as finding a song quickly, categorizing, organizing and even listening again when they want etc. Because of this, people tend to find electronic solutions. To index music, most of the researchers use content based information retrieval mechanism since content based classification doesn't need any additional information rather than audio features embedded to it. As well as it is the most suitable way to search music, when user don't know the meta data attached to it, like author of the song. The most valuable application of this audio recognition is copyright infringement detection. Throughout this survey we will present approaches which were proposed by various researchers to detect, recognize music using content base mechanisms. And finally we will conclude this by analyzing the current status of this era. [ABSTRACT FROM AUTHOR]

Proposing a novel approach for monitoring songs for the radio broadcasting channels is very important for the interest of singers, writers and musicians in the musical industry. Singers, writers and musicians have a claim to intellectual property rights for their songs broadcast over all the radio channels. According to this intellectual property rights act singers, writers and musicians should be paid for their songs broadcast over all the radio channels. Therefore we propose a real time audio monitoring approach to solve this problem which includes our own audio recognition algorithm. It is easy to recognize a song, when you provide the original high quality blueprint of the song as input. But we can't expect such kind of audio input from radio channels since lots of transformations are possible before reaching the end user or listener. For example, adding environmental effects such as noise, adding commercials on the song as watermarks, playing more than one song as a chain without adding any silence between them, playing a part of the song, playing same song in various speeds and so on. These transformations cause change in the uniqueness of particular song and make the problem even more difficult. The algorithm we proposing is resistant to noise and distortion as well as it is capable of recognizing short segment of song when broadcasting over the radio channels. At the end of the processing our system generates a descriptive report including title of the song, singer of the song, writer of the song, composer of the song, number of times it was played and when it was played for all songs for a particular period for all radio broadcasting channels. We evaluate our system against various types of real time scenarios and achieved overall higher level of accuracy (96%) at the end. [ABSTRACT FROM AUTHOR]