![]() To do so, we want to perform an automatic global tempo estimation task and a genre classification task based on rhythm. We propose a rhythmic analysis of what defines certain musical genres including those of EDM. This type of music often dedicated to dance is characterized by its rhythmic structure. The advent of technology dedicated to the arts has allowed the emergence of new musical trends generally described by the term "Electronic/Dance Music" (EDM) which encompasses a plethora of sub-genres. In this survey paper, we provide a review of previous techniques that focuses on optimized data annotation and labeling for video, audio, and text data.Īutomatic detection of the rhythmic structure within music is one of the challenges of the "Music Information Retrieval" research area. ![]() Therefore, researchers started to pay more attention on auto annotation and labeling. However, large amounts of annotated data are still demanded to build robust models and improve the prediction accuracy of the model. Even transferring previous knowledge from a source domain reduces the amount of data needed in a target domain. Transfer learning was designed and widely used as an efficient approach that can reasonably reduce the negative impact of limited data, which in turn, reduces the data preparation cost. ![]() As a result, researchers started to focus on reducing data annotation and labeling costs. However, labeling large amounts of data increases the monetary cost in machine learning. Data labeling has always been one of the most important tasks in machine learning. Machine learning has been utilized to perform tasks in many different domains such as classification, object detection, image segmentation and natural language analysis.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |