Abstract
With recent advances in artificial intelligence, recurrent neural networks have successfully generated pleasing melodies; however, they have struggled to create a full song that has structure, theme, and uniqueness. To overcome this limitation, we introduce Deep Composer, a music generation system based on music retrieval using deep neural hashing to encode the music building blocks. Music generation is performed by using the current music segment to retrieve the next segment from the database until the whole composition is complete. We present performance comparisons with multiple recent state-of-the-art music generation methods to show that the songs generated by Deep Composer are unique, musically pleasing and contain more structure and theme features like that of a professionally composed song.