2019 - Ph.D. in Linguistics, The Graduate Center of the City University of New York.
Daniel´s PhD research centered on the diversity of learned acoustic systems and how, in spite of this diversity, recurrent sound patterns arise. He focused on spoken human language, house finch song, and budgerigar warble.
2012 - M.A. in Applied Linguistics, Columbia University.
2008 - B.A. in History and Spanish, University of Central Arkansas.
Research comparing human and non-human animal communication has made great strides over the past half-century, yet, aspects of vocal behavior remain unexplored. In non-human animal vocal behavior, the smallest unit of analysis is the syllable or breath group, where intakes of breath divide the acoustic stream. Humans, however, can utter full words, phrases, and even sentences between intervals of silence. If alien researchers used the breath group as the smallest domain of analysis in human vocal behavior, they would be confused as to how the phrases “five spiders” and “more than four spiders” elicit somewhat similar responses but “five spiders” and “five ciders” are treated completely differently. In humans, segments – units that build words and phrases and are divided by acoustic transitions rather than silent intervals – are central to our understanding of language and have clarified the extent and limits to cross-population variability, how humans categorize acoustic stimuli, how languages change over time, and how learning and biology interact to create culture. Because of the central role in understanding language, segment analyses can greatly enhance our understanding of animal vocal behavior, as well.
As part of Dan's Marie Skłodowska-Curie fellowship (Segments in Animal Vocalizations, or SEGVOC), he, Dr. Marisa Hoeschele, and colleagues at the Acoustic Research Institute are further developing tools, methods, and experimental protocols to study the production and perception of non-human vocal segments. This includes software that permits users to automatically divide animal vocalizations into segmental units, machine learning models to cluster segment types, and psychoacoustic experiments to determine the perceptual boundaries of segment types. The experimental work in the SEGVOC project focuses on the budgerigar, a small parrot species native to Australia. In particular, Dan is investigating the production of plosive-like segments in budgerigars and if they are produced via the same mechanisms as human plosive segments (sounds like p, d, k, etc.). Furthermore, how do budgies perceive their own plosive sounds? Budgerigars perceive human plosives as categorical, even when the acoustic differences are gradient (Dooling, et al., 1989). Is this true of their own plosive segments? The work in SEGVOC expands on Mann and Hoeschele's previous research with the vocalizations of budgerigars (a small parrot species). Using a segmental approach, they found that humans and budgerigars share organizational biases in how segments are ordered (Mann et al., 2020).
Dan is also employed as a post-doctoral researcher in computational behavioral biology with the Fusani Lab. Here he works on projects related to avian courtship behavior, automated behavioral tracking, and the relationship between hormones and behavior in migratory songbirds.