Deep learning model using squeezenet and promoted ideal gas molecular motion for music genre classification from audio spectrograms. [PDF]
Xue M.
europepmc +1 more source
Mother, Musician, Performer: Living the Impossible?
ABSTRACT This article draws on 19 qualitative in‐depth interviews with classically trained musicians in Australia and the UK, who have an active performing career and identify as mothers. Building on pioneering research on motherhood, work, and leadership in the creative industries, this article explores how mothers navigate the challenges of a ...
Sally Savage, Christina Scharff
wiley +1 more source
Dialogism in publicity discourses of Anglo-American and Chinese universities: A comparative analysis based on Engagement System. [PDF]
Zheng L.
europepmc +1 more source
‘reportless places’: Janet Malcolm and Collage
Critical Quarterly, EarlyView.
Natalie Ferris
wiley +1 more source
“THE NORMAL EXCEPTION”: EDOARDO GRENDI, MICROANALYSIS, AND GENERALIZATIONS*
ABSTRACT “The normal exception” has long been a slogan of microhistory. This oxymoronic phrase is the iconic rendering of an incidental sentence that appeared in a 1977 article by Edoardo Grendi. His article, titled “Micro‐analisi e storia sociale” (Microanalysis and Social History), is cited more often than it is read.
FRANCESCA TRIVELLATO
wiley +1 more source
A novel approach for music genre identification using ZFNet, ELM, and modified electric eel foraging optimizer. [PDF]
Zhang S, Sun Z, Jafari H.
europepmc +1 more source
Zen in the art of insult: notes on the syntax and semantics of abusive speech in Late Middle Chinese [PDF]
Anderl, Christoph
core
ABSTRACT The current study set out to contribute to the burgeoning research area of out‐of‐class L2/FL learning by examining, specifically, English learners’ extramural engagement with watching movies/videos and/or listening to songs (i.e., exposure to audiovisuals).
Art Tsang, Susanna Siu‐sze Yeung
wiley +1 more source
"RaagaDhvani: A novel augmented multi-feature dataset: Advancing emotion recognition in Carnatic music with multimodal features and hybrid deep learning". [PDF]
Priyadarshini A, Divakarla U.
europepmc +1 more source

