The present paper investigates how stress affects lexical decision time in Portuguese, a language where, like English, three stress positions are available: antepenult (APU), penult U). In Portuguese, however, antepenult stress is the least frequent pattern, followed by final and penult stress (Bisol 1994, Wetzels 2007). If more frequent stress patterns correlate with faster lexical decision (mirroring word frequency effects), words with APU should yield longer RTs than words with PU and U stress. In this paper, I show that the opposite is true, and propose an alternative explanation for the effects of stress on lexical decision. The explanation stems from the point at which one computes segmental and suprasegmental information.
Ling-tea returns this week with three presentations from the P-labs:
Who: Guilherme Garcia, Michael McAuliffe, and Hannah Cohen
When: Tuesday, February 16th from 1:00 – 2:00
Where: Ling 117
Guilherme Garcia: Computing segmental and suprasegmental information in lexical decision
Several studies on word recognition have shown that lexical/segmental information significantly affect speakers’ reaction time (RT) when deciding whether a word is real or not (e.g., Cutler & Butterfield 1992, Vitevitch & Luce 1998). Another known effect is neighbourhood density, in that words with more competitors tend to result in longer RT (cf. Vitevitch and Rodríguez 2004). The location of word stress has also been shown to impact lexical access: Vitevitch et al. 1997 show that word-initial stress tend to result in faster RTs for English speakers. However, given the positional bias for word-initial stress in the English lexicon (Cutler and Carter 1987, Cutler and Norris 1987) and the fact that information near the left edge of words makes it a better cue for word recognition (Horowitz et al. 1968, 1969), it is not possible to accurately determine the reason why earlier stress correlates with faster RTs in English. For that, one needs a language with no bias towards word-initial stress.
Michael McAuliffe: Annotating VOT in seven large speech corpora using Speech Corpus Tools
I present a brief overview of the methodology and some preliminary results from the class project of Phonology 4. Students in the class are each annotating VOT (voicing during closure and burst/aspiration) in a language from the GlobalPhone corpus. Annotation is done through a graphical interface in Speech Corpus Tools, which automatically saves changes to a centralized database. In addition to a walkthrough of the interface, I will present some preliminary cross linguistic findings from the first mini project of the class.
Hannah Cohen: TBA
Come on by! Cookies will be provided.
If you want to present at Lingtea, whether it be to work through a difficult problem in your research, to prepare for a conference, or just to update the department on what you’ve been working on, email Colin at email@example.com. Only four slots remain for Winter 2016:
March 22nd, 29th
April 19th, 26th