I am a linguist and neuroscientist studying the organization and representation of human speech sounds in the brain. I am interested in the perception, production, and processing of linguistic prosody (e.g. stress, intonation) and other suprasegmentals such as tone. My research integrates insights from linguistic theory and typology with computational and experimental methods from laboratory phonology, neuroscience, and psychology. As a linguist, I work to model the diversity of phonological patterns found in the languages of the world, and as a neuroscientist, I take an integrative, systems-level approach to understanding the neural mechanisms underpinning spoken language processing.
The long-term objective of this project is to understand the representation of phonological units in the brain and the relationship between those units, auditory sensory input, and higher levels of language organization, namely morphology. To approach this objective, this research uses methods from topological data analysis (TDA) to systematic analyze the distinction between acoustic signal and phonemic contrast in superior temporal gyrus (STG) of patients with clinical intracranial electrode implants.
Typological predictions made by different rule-based and constraint-based theories derive from the mathematical structure of the formalisms themselves. This project applies concepts from algebra and category theory to investigate the mathematical foundations of Harmonic Grammar, Optimality Theory, and SPE-style rule-based phonology in the interest of uncovering abstract invariant structure shared across formalisms.
Phonological patterns can be categorized by the minimal computational expressivity required to describe them. Using methods from formal language theory, this research aims to accurately define the apparent upper bound of expressivity required for the description of phonological patterns and to explain the uneven distribution of patterns over the range of expressivity classes in terms of their relative learnability. (Joint work with Eric Bakovic, Eric Meinhart, and Adam McCollum.)
Ja'a Kumiai is an endangered Yuman language spoken in Baja California, Mexico. The language has a rich syllable inventory, where stressed syllables may have up to four onset segments and two coda segments. Excrescent vowels appear to intervene unpredictably in these complex consonant clusters but do not impact morphophonological processes that target specific syllable positions, such as causitive formation. This project investigates the interaction of these excrescent vowels with syllable structure, stress, and morphology.
Phonologically opaque counterbleeding processes are difficult to model in constraint-based optimization frameworks with parallel evaluation of candidates. This work uses Gradient Symbolic Compution (GSC), a dynamical framework, to model a classic counterbleeding pattern in Yowulmne Yokuts and investigates the typological implications of the GSC system. (Joint work with Eric Bakovic and Matt Goldrick).
The goal of this project is to develop a database and framework for the study of prosodic organization in rhythmically complex rap verse. To adequately account for microtiming in styles of rapped verse which are more speech-like in their delivery than song-like, verses analysed in this project are annotated in Praat TextGrids using visual spectrogram cues. The verses being analysed as part of this project are delivered by emcees JAY-Z, Missy Elliott, Kanye West, and Nicki Minaj.
|under review||A. McCollum, E. Bakovic, A. Mai, E. Meinhardt. The expressivity of segmental phonology and the definition of weak determinism. [pdf]|
|under revision||A. Mai. Phonetic effects of onset complexity on the English syllable. [pdf]|
|2018||A. Mai, A. Aguilar, & G. Caballero. Ja'a Kumiai.Journal of the IPA. [pdf]|
|SCiL 2018||A. Mai, E. Bakovic, M. Goldrick. Phonological opacity as local optimization in Gradient Symbolic Computation. [poster][abstract]|
|ASA 2017||A. Mai. Phonetic effects of onset complexity on the English syllable. [poster]|
|SCAMP 2017||A. Mai, M. Garellek. Tone and phonation in Green Mong song. [poster]|