Translations
A data-visualization experiment - hand-translating Asian Kung-Fu Generation lyrics from Japanese, and charting the effort.
Part language-learning, part analysis - I hand-translate the lyrics of my favourite band and chart the effort as I go.
- Google Sheets: primary data source for study times and metadata.
- Spotify API: song names and track lengths.
- Flask (Python), HTML / CSS, JavaScript.
Asian Kung-Fu Generation is a Japanese alt-rock band from Yokohama - and my favourite band. Translating their lyrics is how I practise the language and scratch the itch to measure things. Here’s how a song goes:
- Write the lyrics out by hand, highlight the words I don’t know, and break them apart. Example.
- Run a script to pull out features - track length, unique character count, minutes spent.
- Look for patterns: am I getting faster, and which songs fought back hardest?
Efficiency (min/char) over translation order. Downward trend = improving. Select a point for the song name.
Raw minutes spent on each translated song.
Unique character count vs. minutes spent translating. Select a point for song details.
Minutes spent per unique character, per song. Lower is more efficient.