Blog Post #3

Hello, and welcome to the third blog post of my senior project! In this post, I will go over my project’s dataset and plan out the preprocessing steps to make it useful in my program.

First, I will need to choose a dataset. After ample research, I chose the GuitarSet dataset developed at the Music and Audio Research Lab and NYU. This dataset contains recordings of musical excerpts played on an acoustic guitar, along with time-aligned annotations of pitch contours, string and fret positions, chords, beats, downbeats, and playing style (for more information about the dataset, see https://tomxi.weebly.com/uploads/1/2/1/6/121620128/xi_ismir_2018.pdf). In order to make this dataset useful for chord recognition, I will first have to preprocess the data. After loading the dataset, visualizing it, and researching its functionality, my advisor and I started pseudo-coding the data preprocessing steps. We plan to extract the relevant spectrogram data from the dataset, which is a visual representation of the audio, and also the time-aligned annotations of the played string-fret combinations. We then will have an array containing the chords played along with a visual representation of the respective audio. This will lay the foundation for creating my model and the rest of my program. 

Next week, I will start implementing these steps in my data preprocessing. Stay tuned!