“Natural” stress patterns and dependencies between edge alignment and quantity sensitivity

We conducted an artificial language learning experiment to study learning asymmetries that might reveal latent preferences relating to, and any dependencies between, the edge alignment and quantity sensitivity (QS) parameters in stress patterning. We used a poverty of the stimulus approach to teach American English speakers an unbounded QS stress rule (stress a single CV: syllable) and either a left- or right-aligning QI rule if only light syllables were present. Forms with two CV: syllables were withheld in the learning phase and added in the test phase, forcing participants to choose between left- and right-aligning options for the QS rule. Participants learned the left- and right-edge QI rules equally well, and also the basic QS rule. Response patterns for words with two CV: syllables suggest biases favoring a left-aligning QS rule with a left-edge QI default. Our results also suggest that a left-aligning QS pattern with a rightedge QI default was least favored. We argue that stress patterns shown to be preferred based on evidence from ease-of-learning and participants’ untrained generalizations can be considered more natural than less favored opposing patterns. We suggest that cognitive biases revealed by artificial stress learning studies may have contributed to shaping stress typology.publishedVersio

The effects of syllable boundary, stop consonant closure duration, and VOT on VCV coarticulation

This study investigated whether the vocalic gestures in VCV sequences are produced with a single diphthongal movement as predicted by the superimposition model of coarticulation or as separate events as predicted by a phoneme-by-phoneme view. ‘Troughs’ or discontinuities in anticipatory vowel-to-vowel coarticulation during the closure period of bilabial stops in symmetrical VCV sequences have provided evidence in favor of a phoneme-by-phoneme view. This investigation sought to uncover the acoustic correlates of troughs in VCV utterances produced by five English and two Persian speakers. Acoustic evidence for troughs was found in frequency changes of F2 transitions in symmetrical [V.bV] and [V.phV] sequences. F2 transitions indicative of tongue-related trough effects were influenced by the syllabic affiliation of the intervocalic stop and to a lesser degree by its voicing properties. Changes in consonantal closure duration did not elicit troughs. Locus equations (LE) were employed as a second methodology to uncover the acoustic correlates of troughs in a variety of consonantal and vocalic contexts. LE slopes capture CV coarticulation. Troughs would be expected to lower slope values. Consistently lower LE slopes at the CV2 interface were observed with closed versus open and voiceless versus voiced stops. LE slopes remained stable across changes in consonantal closure duration. Bidirectional V-to-V coarticulatory effects were also explored. The superimposition model predicts no changes in V-to-V coarticulation as a function of the syllabic affiliation, closure duration, and the voicing properties of an intervocalic stop. Results showed reduced anticipatory V-to-V effects in closed versus open, geminate versus singleton, and voiceless versus voiced conditions in English and with lesser degrees of consistency in Persian. Increased carry-over V-to-V effects were observed in closed versus open syllables in English and in voiceless versus voiced conditions in Persian. Carry-over effects were generally smaller in geminate versus singleton utterances in English and Persian and across voiceless versus voiced stops in English. The results of this study support a phoneme-by-phoneme view of segmental organization in which vocalic and consonantal gestures are distinct, but temporally and spatially overlapping events and affect one another in varying degrees based on the degree of their overlap.Linguistic

Translators’ introduction

National Foreign Language Resource Cente

JAMMU AND KASHMIR BURUSHASKI: LANGUAGE, LANGUAGE CONTACT, AND CHANGE Committee:

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