Audio Music Monitoring: Analyzing Current Techniques for Song Recognition and Identification

Abstract

Abstract-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.

Analysis of Computer Visualized Sound Parameters of Vocal Music Singing Based on Deep Learning

“…Aubin and Bremond put forward a method of similarity measurement based on Aubin pitch and rhythm information and Euclidean distance and developed a new vocal music recognition system by using this technology [3]. Senevirathna and Jayaratne divided the process of vocal music recognition into three stages, namely, pitch extraction, melody matching, and note matching and put forward three algorithms for each stage, which combined the results of the three stages to recognize vocal music [4]. Zhang et al pointed out that, in music performance, the speed of the traditional symphony can be changed between the soil topic, subtopics, paragraphs, and even within the phrase.…”

Classification of Engine Type of Vehicle Based on Audio Signal as a Source of Identification

“…Because of this, the classification of sounds has become a very popular topic. Fields of application include, for example: multimedia retrieval [1,2], technology medical problems s [3,4], speech recognition [5], speaker recognition [6,7], urban sound classification [8,9], environmental sound classification [10,11], speech emotion recognition [12], animal sound classification [13,14], detection of mechanical failure [15], and many others. In recognition tasks, the basic issue is what to recognize, in other words, what the inputs of the system are.…”

Classification of Voice Content in the Context of Public Radio Broadcasting

“…Hence, for the purpose of measuring the performance of a broadcast program, radio stations need to monitor the broadcasting content regularly. Broadcast content monitoring helps to verify when and where the broadcast content placed, protect copyrights by knowing precisely how the content is being used, and measure performance across other broadcast channels [2,3,4,5,6]. Therefore, broadcast content monitoring is a necessary thing for radio stations.…”