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Morwaread M Farbood

Biographic Data

ID9620800
NAMEMorwaread M Farbood
GIVEN NAMESMorwaread M
FAMILY NAMEFarbood
SIGNATUREFARBOOD M M
AFFILIATIONSNew York University
VERIFIEDNo
TOTAL WORKS2
TOTAL CITATIONS0
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2023
LATEST PUBLICATION YEAR2025
H-INDEX0
  • Exploring Melodic Contour

    Michal Goldstein, Michal N Goldstein et al.•ARTICLE•Music Perception An Interdisciplina…•2025

    Previous studies investigating common melodic contour shapes have relied on methodologies that require prior assumptions regarding the expected contour patterns. Here, a new approach for examining contour using dimensionality reduction and unsupervised machine-learning clustering methods is presented. This new methodology was tested across four sets of data: two sets of European folk songs; a mixed-style, curated dataset of Western music; and a s…

  • Commentary on Zhou and Fabian (2021)

    Open Access•Morwaread M Farbood, Morwaread Farbood•ARTICLE•Empirical Musicology Review•2023

    This is a commentary on Zhou and Fabian's article, "Velocity and Virtuosity: An Empirical Investigation of Basic Tempo in Contemporary Performances of Two Large-scale Works of Chopin and Liszt"

No prominent works on this page.

  • Commentary on Zhou and Fabian (2021)

    Open Access•Morwaread M Farbood, Morwaread Farbood•ARTICLE•Empirical Musicology Review•2023

    This is a commentary on Zhou and Fabian's article, "Velocity and Virtuosity: An Empirical Investigation of Basic Tempo in Contemporary Performances of Two Large-scale Works of Chopin and Liszt"

  • Exploring Melodic Contour

    Michal Goldstein, Michal N Goldstein et al.•ARTICLE•Music Perception An Interdisciplina…•2025

    Previous studies investigating common melodic contour shapes have relied on methodologies that require prior assumptions regarding the expected contour patterns. Here, a new approach for examining contour using dimensionality reduction and unsupervised machine-learning clustering methods is presented. This new methodology was tested across four sets of data: two sets of European folk songs; a mixed-style, curated dataset of Western music; and a s…

Neuroscience and Music Perception (2 works) · Art (1 work) · Artificial Intelligence (1 work) · Cognitive science (1 work) · Computer Science (1 work) · Diverse Musicological Studies (1 work) · History (1 work) · Melody (1 work) · Music and Audio Processing (1 work) · Music Technology and Sound Studies (1 work)

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