The curious case of competition in Spanish speech production

Abstract

In previous studies in English examining the influence of phonological neighbourhood density in spoken word production, words with many similar sounding words, or a dense neighbourhood, were produced more quickly and accurately than words with few similar sounding words, or a sparse neighbourhood. The influence of phonological neighbourhood density on the process of spoken word production in Spanish was examined with a picture-naming task. The results showed that pictures with Spanish names from sparse neighbourhoods were named more quickly than pictures with Spanish names from dense neighbourhoods. The present pattern of results is the opposite of what has been previously found in speech production in English. We hypothesise that differences in the morphology of Spanish and English and/or the location in the word where phonological neighbours tend to occur may contribute to the processing differences observed in the two languages.

Reconciling phonological neighborhood effects in speech production through single trial analysis

“…First, previous research has been limited to relatively small sets of items in factorial designs with PhND as a between-item manipulation (i.e., comparing performance for words from dense versus sparse neighborhoods; although see Baus et al, 2008, for a cross-linguistic control within "items"). The data set we collected and analyzed is an order of magnitude larger than that of the studies conducted previously (31,980 trials here vs. 1,482 trials in Baus et al, or 1,152 trials in Vitevitch & Stamer, 2006; see however Newman & German, 2005, for testing 1075 individuals on 44 words for a total of 47,300 trials). Second, the data were analyzed with regression models performed at the single trial level, providing a finegrained approach in which the properties of each individual word and participant are considered explicitly.…”

“…Importantly, however, there is also evidence for interference effects (i.e., worse performance for words with many similar sounding words) on naming latencies, (e.g. Vitevitch & Stamer, 2006) and on accuracy measures (e.g. Newman & German, 2005; the evidence will be carefully reviewed later on).…”

“…Vitevitch and Stamer (2006) suggested that the difference between language production performance in Spanish and in English lies in the location within the word where neighbors can be formed in either language (e.g., frequently the rhyme in English, but ofen the onset in Spanish: rhyme vs. onset density). A study by Vitevitch et al (2004) showed that when PhND is controlled, English words with a high number of onset neighbors are produced more slowly than words with few onset neighbors.…”

“…We introduced the variables of the original study (H statistics, age of acquisition, lexical frequency, phoneme length) together with PhND res , summed neighborhood frequency (from the Dutch database CELEX; Baayen et al, 1993), and trial order into a linear mixed-effects model. We used -1000/RT for transforming the latencies as indicated by The Box-Cox test (Box & Cox, 1964 Vitevitch and Stamer's (2006) argument that the effect of PhND may vary depending on specific language properties as mentioned in the Introduction. Part of the General Discussion is dedicated to discuss this possibility (cf.…”

Comparative Analysis of Networks of Phonologically Similar Words in English and Spanish

“…(Note that in the psycholinguistic literature degree is referred to as neighborhood density.) Interestingly, degree has different influences in Spanish compared to English [22,23], suggesting that the same network structure might have a different influence in a different language as a function of other "structural" characteristics that are not captured in current network measures (e.g., clustering coefficient, degree distribution, etc.). Recall that the lexical networks of several languages consisted of a small giant component (which we will refer to as the giant component), several smaller components (which we will refer to as islands), and many non-connected vertices (which we will refer to as lexical hermits [19]).…”