Music covers an important part of our lives and has existed in almost every society and has universal acoustic features. Even though music is a part of our lives, there are so many unknown secrets about it that many researches have been done and continue to be done about music. Many researchers have previously tried to identify the similarities and differences between music existing in various different cultures and to understand the origin of universality. Researchers in the Department of Physics at the Korea Advanced Institute of Science and Technology (KAIST) conducted a study to examine how music-related cognitive functions, namely the musical instinct, arise.
In the study, the research team utilized AudioSet, a large-scale collection of audio data provided by Google, and taught the artificial neural network to learn various sounds. The research found that certain neurons within the network model responded selectively to music, meaning that neurons spontaneously formed that were minimally responsive to a variety of other sounds, such as the sounds of animals, nature, or machines, but were highly responsive to a variety of types of music, including both instrumental and vocal.
Distinct representation of music in deep neural networks trained for natural sound detection without music.
a Example log-Mel spectrograms of the natural sound data in the AudioSet31. b Architecture of the deep neural network used to detect the natural sound categories in the input data. The purple box indicates the average pooling layer. c Performance (mean average precision, mAP) of the network trained without music for music-related categories (top, red bars) and other categories (bottom, blue). n = 5 independent networks. Error bars represent mean +/− SD. d Density plot of the t-SNE embedding of feature vectors obtained from the network in C. The lines represent iso-proportion lines at 80%, 60%, 40%, and 20% levels. Source data are provided as a Source Data file.
Using an artificial deep neural network that models the brain's processing of auditory information, the research shows that music-tuned units can spontaneously emerge by learning natural sound perception even without learning music. In short, the research uses an artificial neural network model to reveal that musical instincts emerge from the human brain without special learning. For more detailed information, you can look at the research article, here is the research link.
It's a really interesting research, and the results of the research are even more interesting. The results show how successful artificially built models with human-like musicality, and artificial intelligence music apps can be and how widely they will be used in the future. Whether we want it or not, AI will be everywhere in the future and it seems that it will be more in the music industry. Frankly, I thought that artificial intelligence would not be very successful in the music industry, but after a lot of research I have examined recently, I started to believe that artificial intelligence will be very successful in the music industry as well. However, I do not yet know whether AI will be more beneficial or harmful to the music industry.
But the only thing I know is that I love music and the most important thing for me is that music touches my heart.
Music is powerful enough to change lives. Enjoy the music and stay with Love.
Question of the Day : What do you think of the research? If you don't have an answer to this question, You can talk about your favorite song or anything related to music in your comment.
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