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ERN: Emerging Researchers National Conference in STEM

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Computational Research on Music & Audio - Achievements and Challenges Ahead

Faculty #71
Discipline: Technology & Engineering
Subcategory: STEM Research

David Heise - Lincoln University


Computational Research on Music & Audio (CRoMA) and the CRoMA Team of Interdisciplinary Collaborators (CRoMA-TIC) were launched at Lincoln University in 2015 with the support of the National Science Foundation through an HBCU-UP award, establishing a research program to study aspects and applications of computational audio signal processing. This effort has facilitated collaborations between students and faculty researchers across a wide array of disciplines (including computer science, engineering, mathematics, psychology, biology, and music) from over a dozen universities. Undergraduates have been intentionally involved in research activities, and students have presented research at national and international conferences. (One such presentation earned a first-place award at the 2017 Emerging Researchers National Conference in STEM.) Two students have successfully defended theses from this research, including one MS thesis and one undergraduate honors thesis. The PI has established a close working relationship with colleagues in biological sciences and continues to develop improved methods for acoustically monitoring pollinators (bumble bees, in particular), work that has important implications for conservation, agriculture, and ecology. The specific work in pollinator monitoring applies more fundamental research to incorporate attention into computational auditory scene analysis, research that has the potential to significantly advance automatic speech recognition, automatic music transcription, technology to mitigate hearing impairments, surveillance activities, and many heretofore unexplored potential applications of acoustic monitoring technology. This poster will summarize the accomplishments of CRoMA-TIC to date, the current state of research in the aforementioned areas, and anticipated directions moving forward.

Funder Acknowledgement(s): National Science Foundation, Award #1410586

Faculty Advisor: None Listed,
NSF Affiliation: HBCU-UP

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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