Paul Olejarczuk
Biographic Data
| ID | 1720008 |
|---|---|
| NAME | Paul Olejarczuk |
| GIVEN NAMES | Paul |
| FAMILY NAME | Olejarczuk |
| SIGNATURE | OLEJARCZUK P |
| AFFILIATIONS | California State University, Chico |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 2 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Effects of Sociophonetic Variability on L2 Vocabulary Learning
Acoustic variability refers to variations in speech that do not alter linguistic content. Previous studies have demonstrated that acoustic variability improves second language (L2) word learning when varying talker, speaking style, or speaking rate but not amplitude or fundamental frequency (Barcroft & Sommers, 2005; Sommers & Barcroft, 2007). The current study examined the effects of region-based sociophonetic variability. In Experiment 1, Engli…
Acoustic correlates of anticipatory and progressive [ATR] harmony processes in Ethiopian Komo
Distributional learning is error-driven
Much previous research on distributional learning and phonetic categorization assumes that categories are either faithful reproductions or parametric summaries of experienced frequency distributions, acquired through a Hebbian learning process in which every experience contributes equally to the category representation. We suggest that category representations may instead be formed via error-driven predictive learning. Rather than passively stori…
The metrical parse is guided by gradient phonotactics
Phonotactic generalisations can be computed at different levels of granularity, from a coarse-grained legal/illegal dichotomy ( blick , dwick ≻ * bnick , * lbick ) to a fine-grained gradient of acceptability ( blick ≻ dwick ≻ bnick ≻ lbick ). This article investigates the sensitivity of the English metrical parse to the granularity of medial onset phonotactics. We present two experiments that feature pseudo-words with medial consonants and CC clu…
Distributional learning is error-driven
Much previous research on distributional learning and phonetic categorization assumes that categories are either faithful reproductions or parametric summaries of experienced frequency distributions, acquired through a Hebbian learning process in which every experience contributes equally to the category representation. We suggest that category representations may instead be formed via error-driven predictive learning. Rather than passively stori…
The metrical parse is guided by gradient phonotactics
Phonotactic generalisations can be computed at different levels of granularity, from a coarse-grained legal/illegal dichotomy ( blick , dwick ≻ * bnick , * lbick ) to a fine-grained gradient of acceptability ( blick ≻ dwick ≻ bnick ≻ lbick ). This article investigates the sensitivity of the English metrical parse to the granularity of medial onset phonotactics. We present two experiments that feature pseudo-words with medial consonants and CC clu…
Acoustic correlates of anticipatory and progressive [ATR] harmony processes in Ethiopian Komo
Effects of Sociophonetic Variability on L2 Vocabulary Learning
Acoustic variability refers to variations in speech that do not alter linguistic content. Previous studies have demonstrated that acoustic variability improves second language (L2) word learning when varying talker, speaking style, or speaking rate but not amplitude or fundamental frequency (Barcroft & Sommers, 2005; Sommers & Barcroft, 2007). The current study examined the effects of region-based sociophonetic variability. In Experiment 1, Engli…
Computer Science (3 works) · Linguistics (3 works) · Phonetics and Phonology Research (3 works) · Psychology (3 works) · Artificial Intelligence (2 works) · Language Development and Disorders (2 works) · Linguistic Variation and Morphology (2 works) · Speech recognition (2 works) · Vocabulary (2 works) · Acoustics (1 work)