@Article{cmc.2020.09362,
AUTHOR = {Oakyoung Han, Jaehyoun Kim},
TITLE = {Analysis and Process of Music Signals to Generate TwoDimensional Tabular Data and a New Music},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {63},
YEAR = {2020},
NUMBER = {2},
PAGES = {553--566},
URL = {http://www.techscience.com/cmc/v63n2/38529},
ISSN = {1546-2226},
ABSTRACT = {The processing of sound signals is significantly improved recently. Technique 
for sound signal processing focusing on music beyond speech area is getting attention due 
to the development of deep learning techniques. This study is for analysis and process of 
music signals to generate tow-dimensional tabular data and a new music. For analysis and 
process part, we represented normalized waveforms for each of input data via frequency 
domain signals. Then we looked into shorted segment to see the difference wave pattern 
for different singers. Fourier transform is applied to get spectrogram of the music signals. 
Filterbank is applied to represent the spectrogram based on the human ear instead of the 
distance on the frequency dimension, and the final spectrogram has been plotted by Mel 
scale. For generating part, we created two-dimensional tabular data for data manipulation. 
With the 2D data, any kind of analysis can be done since it has digit values for the music 
signals. Then, we generated a new music by applying LSTM toward the song audience 
preferred more. As the result, it has been proved that the created music showed the similar 
waveforms with the original music. This study made a step forward for music signal 
processing. If this study expands further, it can find the pattern that listeners like so music 
can be generated within favorite singer’s voice in the way that the listener prefers.},
DOI = {10.32604/cmc.2020.09362}
}