Namaeh Farhangistan

Namaeh Farhangistan

A Typology of Word Stress Based on Language Acquisition and Processing

Document Type : Original Article

Author
Hamed Rahmani
Visiting Assistant Professor, Department of Linguistics, University of Tehran, Tehran, Iran
10.22034/nf.2025.487672.1361
Abstract
Word stress can be examined through the lens of language processing and acquisition algorithms—algorithms that analyze language as a continuous sequence of auditory signals rather than a set of predefined words and labels. This perspective, which considers infants' cognitive characteristics and limitations, reveals new layers of complexity in the way linguistic phenomena are encountered and processed. In this paper, we investigate word stress based on patterns of infant language acquisition from continuous speech, addressing challenges that traditional approaches often overlook, where stress is described with clear-cut lexical boundaries and morphosyntactic labels. We review a cognitive model of stress acquisition developed by Peperkamp and Dupoux, emphasizing its core assumptions and typological predictions. We then explore cross-linguistic differences in stress pattern observability and the accessibility of stress-learning algorithms in languages with phonologically predictable stress patterns, examining distinctions between phonological and morphological predictability. Next, we turn to Persian, focusing on the unique challenges it presents for stress acquisition algorithms and the key questions it raises. Finally, we propose directions for future research on Persian stress, advocating for interdisciplinary collaboration, large-scale collection of naturalistic data, and the application of self-supervised machine learning models.
Keywords
Taxonomy of reliance: language acquisition: reliance processing: word reliance: self
monitored learning: Persian

Subjects

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Namaeh Farhangistan
Volume 24, Issue 2 - Serial Number 96
Nameh Farhangestan (Iranian languages ​​and dialects)
May and June 2025
Pages 99-122

  • Receive Date 15 November 2024
  • Revise Date 28 November 2024
  • Accept Date 20 January 2025