Speaker: Paula Lauren
Music Information Retrieval (MIR) is an interdisciplinary field that focuses on the extraction, analysis, and organization of information from music data using computational methods. Several MIR subfields including music similarity analysis, cover song identification, genre classification, and music emotion recognition will be explored. Preliminary research in these aforementioned MIR disciplines has been conducted to better understand the contributions and limitations. This talk will also explore MIR methodologies and tools for examining the differences between cover songs and their originals as well as artistic reinterpretations. The research also includes preliminary exploration using several MIR tools such as MIRtoolbox for Matlab and Librosa for Python. The vision of this research has several implications such as advancing music education practices, expanding creative possibilities for artists, providing insights into music cognition, and refining music recommendation systems.