Generating Embeddings for Audio Files and Metadata of Songs

Metadata embeddings with BERT embedding model

To use BERT for generating metadata embedding, we need to convert the tabular metadata information (attributes and values) of a song into a string, which we call the textual_description of the song. For example:

"The song Infinity Edge has a danceability of 0.528, energy of 0.847, loudness of -4.741, speechiness of 0.0307, acousticness of 0.00674, instrumentalness of 0.814, liveness of 0.12, valence of 0.389, tempo of 143.997."

To do this, we read the CSV file containing metadata about songs and create descriptive text for each song using its attributes and values. We add this text to the DataFrame and then save the updated DataFrame back to the CSV file.