gpt_outline.md

To create a model that can input guitar tunes from a specific artist and produce corresponding guitar tabs, you can follow these general steps:

Data preparation:

Convert the mp3 files to a more suitable format, such as MIDI or MusicXML, which contains more structured information about the music, like pitch, duration, and timing. You can use tools like "audio-to-midi" converters or "Melodyne" to do this. For the guitar tabs, use a standardized format like Guitar Pro, Power Tab, or ASCII tablature. This will make it easier to parse and represent the information.

Data preprocessing:

Create a dataset of pairs of audio features and corresponding guitar tabs. For the audio features, you can use techniques like Mel-frequency cepstral coefficients (MFCCs) or chroma features that capture pitch and timbre information. Tokenize the guitar tabs to represent them in a format that can be used as input to the model. For ASCII tabs, you can tokenize them into characters or words, while for more structured formats like Guitar Pro, you can use dedicated libraries to parse the files and create custom tokens.

Model selection and training:

Choose a suitable model architecture for the task, such as a sequence-to-sequence (seq2seq) model, which is often used for tasks involving translating one sequence into another (e.g., machine translation). In this case, the model would translate audio features into guitar tabs. Train the model on the dataset you created in the preprocessing step. It's important to use a large and diverse dataset, as this will improve the model's ability to generalize to new, unseen data.

Model evaluation and fine-tuning:

Evaluate the model's performance using metrics like BLEU score or edit distance, which measure how well the generated tabs match the ground truth. Fine-tune the model using techniques like transfer learning or domain adaptation to improve its performance on the specific artist you are interested in.

Deployment and usage:

Deploy the trained model in a suitable environment, such as a web application or a mobile app, where users can input guitar tunes and receive the generated guitar tabs. For storing the tabs as input, you can use any file format that is easily parseable and well-structured, such as Guitar Pro, Power Tab, or ASCII tablature. You'll need to tokenize the tabs and convert them into a suitable format for feeding into the model, like a list of integers or one-hot encoded vectors.