HarmonicAI is an AI-powered acoustic guitar chord recognition system that utilizes signal processing techniques and machine learning algorithms to analyze audio features and identify the chords being played on an acoustic guitar.

• Efficiently identify the chords being played on an acoustic guitar in real-time.
• Highly accurate and optimized for speed.
• Built using Python and various machine learning libraries such as TensorFlow, Keras, and Scikit-learn.
• A web application to run the final product.

Currently the Isophonics dataset [available at http://isophonics.net/datasets] has been identified as one of the best options for this project. This is has been done for several reasons which include:

1. Large and diverse dataset: The Isophonics dataset contains a large and diverse collection of popular music that spans multiple genres and decades. This diversity ensures that the dataset is representative of the types of songs and guitar chords that you might encounter in the real world.
2. High-quality annotations: The Isophonics dataset has been manually annotated with chord labels by expert musicians, which ensures that the labels are accurate and reliable. The annotations also include information about chord duration and onset, which can be used to train more complex models that take into account the temporal aspects of the music.
3. Widely used in research: The Isophonics dataset has been widely used in research on automatic chord recognition, and many state-of-the-art algorithms have been trained on this dataset. This means that you can compare your results to other published results and assess the performance of your model relative to other approaches.
4. Open-source and free: The Isophonics dataset is open-source and free to use, which makes it accessible to researchers and hobbyists alike.