Research Projects
My interdisciplinary academic background and skill sets, encompassing audio engineering, coding, music composition, and performance, grant me a distinctive perspective in music research, closely aligned with digital humanities. Half of my work is dedicated to critical sound studies, where I explore the philosophy of music and sound-oriented "products", and delve into how people perceive and interact with them. The other half of my research is more technical, concentrating on discovering and processing "musical patterns", which range from melodic motifs in soundtracks, orchestration styles that define genres, to unique symbols in musical notation, and many more, yet to be explored.
01
Challenges In Designing Sound Maps
Through critical analysis of influential sound maps, this paper sets out to identify and analyze three fundamental challenges intrinsic to the design of sound maps: (1) the use of pre-existing cartographic layers, (2) the temporal inconsistencies in location data, and (3) departures from mapping goals in sound maps. It then further investigates strategies for effectively disseminating information by synergistically merging auditory elements with contemporary cartographic techniques, each tailored to address one of the specific challenges under scrutiny.
#sound studies #cartography #sound map # phonography
02
Finding Connectivity:
A Survey of Musical Pattern Processing at the Confluence of Cognitive Neuroscience and Machine Learning
The paper aims to identify core components of a musical pattern and then introduces cognitive mechanisms involved in musical perception and pattern recognition, focusing specifically on “pattern-rich” music in the survey. Subsequently, the discussion shifts to how these cognitive insights have spurred innovations in algorithm design. The paper evaluates key algorithms for musical feature extraction and genre classification, detailing their foundation in neural mechanisms. The strengths and limitations of these algorithms are compared to human processing abilities, setting the stage for future explorations in cognitive neuroscience and AI in the realm of musical pattern analysis.
#pattern recognition #machine learning #music cognition # ann
04
Water Talks:
A Sound Map Dedicated to the Baltimore Inner Harbor
This project is a data-driven study of the soundscapes around Baltimore's Inner Harbor. I am currently developing a sound map designed to diagnose the area's noise issues. This system incorporates data from my field recordings and integrates it with ArcGIS and other city data released by public administrations for geospatial analysis.
#geospatial analysis #field recording #python #data analysis #soundmapping
