Digital Humanities represents the intersection between the Humanities/Arts and Data Science research methods.
In this session we will demonstrate resources and tools used to analyze audio and text from transcribed lyrics
|Omnizart Colab Implementation||Omnizart is a Python library that aims for democratizing automatic music transcription. Given polyphonic music, it is able to transcribe pitched instruments, vocal melody, chords, drum events, and beat. This is powered by the research outcomes from Music and Culture Technology (MCT) Lab.||
Transcribe vocals from a class-selected YouTube video into a table containing time stamp, pitch, and frequency.
|Gale Digital Scholar Lab||The Gale Digital Scholar Lab makes digital humanities accessible to everyone and approachable to those new to the field. Advanced features support researchers already deep into their digital humanities journey.||Create and analyze corpus of transcribed text of music lyrics from the Religions of America archive.|
|Voyant Tools||Voyant Tools is a web-based text reading and analysis environment. It's designed to make it easy for you to work with your own text or collection of texts in a variety of formats, including plain text, HTML, XML, PDF, RTF, and MS Word.||
Select a work from Project Gutenberg