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- Volume 49, Issue 1, 2023
Concentric - Volume 49, Issue 1, 2023
Volume 49, Issue 1, 2023
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Perceptual effects on the interpretation of English stops by Taiwan Mandarin speakers
Author(s): Mingchang Lü (呂明昌)pp.: 1–36 (36)More LessAbstractGiven relevant experimental evidence and language universals, this paper investigates the adaptation patterns of English stops in Taiwan Mandarin and argues in favor of the substantial existence of the perceptual phase in loanword adaptation, counter to Paradis & Tremblay’s (2009) phonological view on a similar issue. The statistically based results from a corpus of established loanwords support the view that interpretation of foreign stops is largely conditioned by a handful of perceptual factors, i.e., syllable position, aspiration and voicing, sonority, and the masking effect of [s]. These effects serve as part of the perceptual cues and function with the structural constraints at the level of perception, which generates an underlying representation that awaits evaluation at the level of production.
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Effects of language familiarity, utterance length, and speech quality in prosodic boundary identification
Author(s): Chen-Hsiu Grace Kuo (郭貞秀)pp.: 37–69 (33)More LessAbstractThis study investigates the effects of several stimulus sources: language familiarity, utterance length, and speech quality, on listeners’ predictions of the sizes of the upcoming prosodic boundaries. Experiments with native Taiwanese speakers were conducted, and the stimuli varied in prosodic boundary units (i.e., word, phrase, and sentence), languages (i.e., Taiwanese, English, and Swedish), utterance lengths (i.e., 2-second, and 2 syllables; the latter is approximately 0.416-second long), and speech qualities (i.e., normal speech, low-pass filtered speech). Results showed that: (a) listeners performed better when the utterances were longer; (b) listeners performed better in low-pass filtered speech when they had no prior knowledge of the target language; (c) there was a tendency for the language familiarity effect, but this effect was heavily influenced by the extent of similarity of the phonetic realizations in different prosodic boundaries, and the listeners’ language proficiency which was associated with working memory storage capacity.
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An experimental investigation of P/Case‑drop in Korean gapping
Author(s): Jeong-Seok Kim (金正錫)pp.: 70–95 (26)More LessAbstractThis study examines two syntactic analyses of P/Case-drop in Korean gapping (aka right-node-raising or right-peripheral ellipsis): LF copying (Abe & Hoshi 1997) and PF deletion (Kim 1997). We employ two online acceptability rating experiments to investigate to what extent the distribution of P/Case-drop is controlled by grammatical and extra-grammatical constraints. The experimental findings suggest that (a) linear non-parallelism elicits a processing cost for gapping and (b) P/Case-drop is a costly operation, which results in higher frequencies of PP fragments (in relation to NP fragments) and Case-marked NP fragments (in relation to Case-less NP fragments). We argue that the parallelism effect follows from the parser’s general preference to keep the structure of each conjunct maximally parallel in a coordination structure (Kim et al. 2020). Given this, we conclude that P/Case-drop phenomena in Korean gapping are better explained by a PF deletion analysis, supplemented with extra deletion (An 2016, 2019; Erschler 2022) and ellipsis parallelism (Frazier, Munn & Clifton 2000; Kehler 2000; Frazier & Clifton 2001; Carlson 2002), rather than by an LF copying analysis.
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Incorporating structural topic modeling into short text analysis
Author(s): Po-Ya Angela Wang (王伯雅) and Shu-Kai Hsieh (謝舒凱)pp.: 96–138 (43)More LessAbstractThe past few decades have seen the rapid development of topic modeling. So far, research has been more concerned with determining the ideal number of topics or meaningful topic clustering words than with applying topic modeling techniques to evaluate linguistic theories. This study proposes the Structural Topic Model (STM)-led framework to facilitate the interpretation of topic modeling results and standardize text analysis. STM encompasses various model training mechanisms, thereby requiring systematic designs to properly combine language studies. “Structural” in STM refers to the inclusion of metadata structure. Unlike the corpus-based keyness approach, STM can capture contextual cues and meta-information for the interpretation of topical results. Besides, STM can make cross-corpora comparisons via topical contrast, a challenging task for corpus-driven related models such as the Biterm Topic Model (BTM). Stylistic variations in song lyrics are taken as an illustration to show how to use the suggested framework to delve into the linguistic theory proposed by Pennebaker (2013). The topical model and iterable model in the proposed paradigm can clarify how pronouns affect style distinction. We believe the proposed STM-led framework can shed light on text analysis by conducting a reproducible cross-corpora comparison on short texts.
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