A web-based interface to calculate phonological neighborhood density for words and nonwords in Modern Standard Arabic

The availability of online databases (e.g., Balota et al., 2007) and calculators (e.g., Storkel & Hoover, 2010) has contributed to an increase in psycholinguistic-related research, to the development of evidence-based treatments in clinical settings, and to scientifically supported training programs in the language classroom. The benefit of online language resources is limited by the fact that the majority of such resources provide information only for the English language (Vitevitch, Chan & Goldstein, 2014). To address the lack of diversity in these resources for languages that differ phonologically and morphologically from English, the present article describes an online database to compute phonological neighborhood density (i.e., the number of words that sound similar to a given word) for words and nonwords in Modern Standard Arabic (MSA). A full description of how the calculator can be used is provided. It can be freely accessed at https://calculator.ku.edu/density/about.

Exploring How Phonotactic Knowledge Can Be Represented in Cognitive Networks

In Linguistics and Psycholinguistics, phonotactics refers to the constraints on individual sounds in a given language that restrict how those sounds can be ordered to form words in that language. Previous empirical work in Psycholinguistics demonstrated that phonotactic knowledge influenced how quickly and accurately listeners retrieved words from that part of memory known as the mental lexicon. In the present study, we used three computer simulations to explore how three different cognitive network architectures could account for the previously observed effects of phonotactics on processing. The results of Simulation 1 showed that some—but not all—effects of phonotactics could be accounted for in a network where nodes represent words and edges connect words that are phonologically related to each other. In Simulation 2, a different network architecture was used to again account for some—but not all—effects of phonotactics and phonological neighborhood density. A bipartite network was used in Simulation 3 to account for many of the previously observed effects of phonotactic knowledge on spoken word recognition. The value of using computer simulations to explore different network architectures is discussed.

Lexical and Phonetic Influences on the Phonolexical Encoding of Difficult Second-Language Contrasts: Insights From Nonword Rejection

Establishing phonologically robust lexical representations in a second language (L2) is challenging, and even more so for words containing phones in phonological contrasts that are not part of the native language. This study presents a series of additional analyses of lexical decision data assessing the phonolexical encoding of English /ε/ and /æ/ by German learners of English (/æ/ does not exist in German) in order to examine the influence of lexical frequency, phonological neighborhood density and the acoustics of the particular vowels on learners’ ability to reject nonwords differing from real words in the confusable L2 phones only (e.g., *l[æ]mon, *dr[ε]gon). Results showed that both the lexical properties of the target items and the acoustics of the critical vowels affected nonword rejection, albeit differently for items with /æ/ → [ε] and /ε/ → [æ] mispronunciations: For the former, lower lexical frequencies and higher neighborhood densities led to more accurate performance. For the latter, it was only the acoustics of the vowel (i.e., how distinctly [æ]-like the mispronunciation was) that had a significant impact on learners’ accuracy. This suggests that the encoding of /ε/ and /æ/ may not only be asymmetric in that /ε/ is generally more robustly represented in the lexicon than /æ/, as previously reported, but also in the way in which this encoding takes place. Mainly, the encoding of /æ/ appears to be more dependent on the characteristics of the L2 vocabulary and on one’s experience with the L2 than that of its more dominant counterpart (/ε/).

Input effects in the acquisition of verb inflection: Evidence from Emirati Arabic

This study investigates the acquisition of the Imperfective verb inflection paradigm in Emirati Arabic (EA), to determine whether the learning process is sensitive to the phonological and typological properties of the input. We collected data from 48 participants aged 2;7 to 5;9 years, using an elicited production paradigm. Input frequencies of inflectional contexts, verb types and tokens were obtained from corpora of child-directed and adult EA. Children's accuracy was inversely related to the input frequency of inflectional contexts, but not related to type and token frequency or phonological neighborhood density. Token frequency interacted with age, such that younger children performed considerably worse on low-frequency tokens, but older children performed equally well on high- and low-frequency tokens. We conclude that learning is input-driven, but that a sufficiently regular paradigm allows children to eventually generalise across all items earlier than in previously studied European languages.

Phonological neighborhood measures and multisyllabic word acquisition in children

Multisyllabic words constitute a large portion of children's vocabulary. However, the relationship between phonological neighborhood density and English multisyllabic word learning is poorly understood. We examine this link in three, four and six year old children using a corpus-based approach. While we were able to replicate the well-accepted positive association between CVC word acquisition and neighborhood density, no similar relationship was found for multisyllabic words, despite testing multiple novel neighborhood measures. This finding raises the intriguing possibility that phonological organization of the mental lexicon may play a fundamentally different role in the acquisition of more complex words.

Comparing Lexical Cues in Listener Processing of Dysarthria and Speech in Noise

Purpose The frequency of a word and its number of phonologically similar neighbors can dramatically affect how likely it is to be accurately identified in adverse listening conditions. This study compares how these two cues affect listeners' processing of speech in noise and dysarthric speech. Method Seven speakers with moderate hypokinetic dysarthria and eight healthy control speakers were recorded producing the same set of phrases. Statements from control speakers were mixed with noise at a level selected to match the intelligibility range of the speakers with dysarthria. A binomial mixed-effects model quantified the effects of word frequency and phonological density on word identification. Results The model revealed significant effects of word frequency ( b = 0.37, SE = 0.12, p = .002) and phonological neighborhood density ( b = 0.40, SE = 0.12, p = .001). There was no effect of speaking condition (i.e., dysarthric speech vs. speech in noise). However, a significant interaction was observed between speaking condition and word frequency ( b = 0.26, SE = 0.04, p < .001). Conclusions The model's interactions indicated that listeners were more strongly influenced by the effects of word frequency when decoding moderate hypokinetic dysarthria as compared to speech in noise. Differences in listener reliance on lexical cues may have important implications for the selection of communication-based treatment strategies for speakers with dysarthria.