Arsenault, Paul

 

Dr. Paul Arsenault is Associate Professor of Linguistics.

PhD, University of Toronto, 2012.

MA, University of Hyderabad, India, 2002.

SIL Linguistic Training, Canada Institute of Linguistics, 1998.

BTh, Master's College and Seminary (formerly EPBC), 1995.

Copyright, Tyndale University. All rights reserved.

Recent Submissions

  • Kalasha (Bumburet Variety) 

    Kochetov, Alexei, 1967-; Arsenault, Paul; Heegård Petersen, Jan; Kalas, Sikandar; Kalash, Taj Khan (Cambridge University PressLondon, UK, 2021-12)

  • Acoustics of Kalasha Laterals 

    Kochetov, Alexei, 1967-; Heegård Petersen, Jan; Arsenault, Paul (American Institute of Physics for the Acoustical Society of AmericaNew York, 2020)
    Kalasha, a Northwestern Indo-Aryan language spoken in a remote mountainous region of Pakistan, is relatively unusual among languages of the region as it has lateral approximants contrasting in secondary articulation—velarization ...

  • Two Types of Retroflex Harmony in Kalasha: Implications for Phonological Typology 

    Arsenault, Paul; Kochetov, Alexei, 1967- (Oxford University PressKarachi, 2022)
    Recent cross-linguistic surveys by Hansson (2001; 2010) and Rose & Walker (2004) have revealed that consonant harmony systems exhibit unique typological properties that set them apart from other assimilation patterns ...

  • Retroflex Consonant Harmony: An Areal Feature in South Asia 

    Arsenault, Paul (De Gruyter MoutonBerlin, Germany, 2015)
    Retroflexion is a well-known areal feature of South Asia. Most South Asian languages, regardless of their genetic affiliation, contrast retroflex consonants with their non-retroflex dental counterparts. However, South Asian ...

  • Retroflexion in South Asia: Typological, Genetic, and Areal Patterns 

    Arsenault, Paul (De Gruyter MoutonBerlin, Germany, 2017)
    Retroflexion in South Asia has been the subject of at least two previous typological studies: Ramanujan and Masica (1969) and Tikkanen (1999). Despite their many virtues, these studies are limited by the size of their data ...