- Notebooks
Three separate notebooks describing the process of getting the data, analyzing the data, and creating the lyric generator the resulting model - /Data
The various files containing the data I collected and used - /helper_functions
Python files that make the notebooks work - /Images
Important images used in the analysis and presentation - streamlit_app.py
Run this file to explore the lyric generator app - Presentation Slide Deck
This projects explores the lyrics behind The Beatles through NLP with NLTK and NMF. Also, there is a lyric generator based on The Beatles using GPT-2 and streamlit.
- Natural Language Processing
- Topic Modeling
- Sentiment Analysis
- NLTK
- NMF
- GPT-2
- Seaborn
- Matplotlib
- Numpy
- Pandas
- JSON
The lyric generator itself is mostly for fun, but the concept of a lyric generator can be used by artists. As a songwriter, I plan on creating my own lyric generator trained on lyrics I've written to help me out when I'm in a rut. As for the analysis, one specific insight popped out, and that was the fact that Ringo as the most negative sentiment on Rubber Soul. I always thought Ringo sang about funny topics, but this proved my assumption wrong.
