Automatic audio sample finder for music creation : Melodic audio segmentation using DSP and machine learning
Abstract: In the field of audio signal processing, there have always been attempts to cre- ate tools which help musicians by automating processes for music creation or analysis, and the electronic music industry is still playing an important role in the combination of software engineering and music. In the age of sample based synthesizers and sequencers, creating and using high quality and unique audio sample packages is a crucial part for composing songs.Nowadays, there are hundreds of audio applications and editors that provide the sufficient tools for songwriters and DJs to find and edit audio samples and create their own signature packages for their performances. However, these applications do not offer automated solutions to extract melodic loop or drum samples. Therefore, the whole procedure of extracting euphonious and unique samples can be quite time consuming. To decide which part of the song is good enough to be used as a separate loop or drum sound is highly subjective, so to fully automate this mechanism is really challenging. However, having a good balance between fully automated processes and freedom for additional editing can result to a useful tool, which can still save a lot of time for the users.In this paper, I present the research and implementation of a cross-platform (Windows, macOS, Linux) desktop application which automatically extracts melodic motifs and percussion sections from songs for loop and drum sam- ples. Furthermore, the app also provides classification of the extracted drum samples in five categories (kick, snare, clap, open hi-hat and closed hi-hat) and allows the user to do additional editing on the samples. The software is devel- oped as a part of an internship at a Swedish audio company, called Teenage Engineering, therefore the application converts the final sample package into a single file which is supported by the company’s OP-Z sequencer and synthe-sizer device.
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