You Peng¹, Ariel Jiang² and Qi Lu³, ¹California State Polytechnic University, USA, ²University of California, USA and ³Department of Social Science University of California, USA

Today, the growing market of entertainment has placed a higher demand for music. Quality music is essential for video making, video game making, or even in any public places. However, sometimes finding a suitable list of music can be hard and expensive. This may be solved by automatic, deep-learning based music making. Using Recurrent Neural Network, computers are able to learn the patterns from existing music pieces and convert them to a possibility map. Companies like Google, Sony, and Amper are creating their applications for music generation. We plan to set up a platform where generating music can be done and retrieved directly online. With different options for genre and length, the users can conveniently generate music that fits their needs.

Music Generation, Machine Learning, RNN, Web Service