Productivity of the broken plural in Maltese

In this research, we examine the productivity of the broken plural in Maltese. Using machine learning techniques and behavioral methods, we show that the broken plural is able to be predicted by a singular noun’s CV structure. Using a logistic regression classifier, we are able to correctly predict the plural CV structure of the singular noun with 69% accuracy when classifying among all available options and 80% accuracy when classifications are restricted by the structure of the singular (32% and 4% respective relative increases over a strong generalized context model (Dawdy-Hesterberg & Pierrehumbert, 2014) baseline). We are further investigating the results obtained from the machine learning using behavioral methods. In a Wug Test (following Berko, 1958), Maltese native speaker participants are shown nonsense words conforming to the CV structures found above, randomly paired with an imaginary animal picture (from Ohala, 1999). Each participant provides a response to the carrier phrase “This is a [wug]. If you saw three of them, you would say, ‘There are three [wugs].’” Using these results together, we will be able to determine whether humans are sensitive to the same features that were useful to the machine learning algorithm. Previous research suggests that humans are sensitive to CV structures when asked to form novel words (e.g., Galea, 2011), and we will expand on those results in Maltese broken plurals. Research showing that some participants are sensitive to the differences in words that sound Semitic vs. those that sound Indo-European (e.g., Twist, 2006; Drake, in prep) may also come into play here; however, it can be seen that broken plurals can be applied to non-Semitic loanwords, such as ġakketta ‘jacket’ ~ ġkieket ‘jackets’. This suggests that using a broken plural productively may not be confined to the Semitic sub-lexicon

The cat stalked ?wilily around the house: Morphological dissimilation in deadjectival adverbs

The adverbial suffix -ly[1] and the adjectival suffix -ly[2] typically do not combine (e.g., *ghost+-ly[1]+-ly[2] 'in a ghostlike manner'). However, phonologically similar strings are attested when one /li/ string is part of the word stem (jollily, compared to: ?smellily, *lovelily). Does morphological structure modulate the acceptability of these words independently from the impact of phonological or usage-based constraints? In two experiments, jolly-type stems are rated more acceptable than smell- and love-type stems, which did not significantly differ from each other. A combination of phonological constraints and increased morphological complexity can account for the observed pattern

Lexical Diversity, Lexical Sophistication, and Predictability for Speech in Multiple Listening Conditions

When talkers anticipate that a listener may have difficulty understanding their speech, they adopt a speaking style typically described as “clear speech.” This speaking style includes a variety of acoustic modifications and has perceptual benefits for listeners. In the present study, we examine whether clear speaking styles also include modulation of lexical items selected and produced during naturalistic conversations. Our results demonstrate that talkers do, indeed, modulate their lexical selection, as measured by a variety of lexical diversity and lexical sophistication indices. Further, the results demonstrate that clear speech is not a monolithic construct. Talkers modulate their speech differently depending on the communication situation. We suggest that clear speech should be conceptualized as a set of speaking styles, in which talkers take the listener and communication situation into consideration

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions

L1 Biases in Learning Root-And-Pattern Morphology

This dissertation addresses the question of whether non-adjacent morphological dependencies are as difficult to learn as non-adjacent phonological dependencies. Non-adjacent dependencies have been investigated in the past, and have proven to be at best difficult to learn (Bonatti, Peña, Nespor, & Mehler, 2005; Gómez, 2002; LaCross, 2011, 2015; Newport & Aslin, 2004), and at worst, completely unlearnable (Newport & Aslin, 2004: experiment 1). LaCross (2011, 2015) showed that speakers of a language employing non-adjacent dependencies were able to learn an artificial grammar employing analogous non-adjacent dependencies easily, suggesting there may be a linguistic bias that makes speakers more aware or capable of unconsciously parsing non-adjacent dependencies so long as they speak a language that employs vowel harmony. The research in this dissertation studies three subject populations with two tasks and two grammars to discover whether speakers of a language utilizing root-and-pattern morphology also have the ability to unconsciously parse non-adjacent dependencies pred- icated on morphological structure. Chapter 2 uses a segmentation or statistical learning task similar to the experiments mentioned above, while Chapter 3 uses a word elicitation task to establish a more fine-grained representation of what experiment participants learn after a very short exposure. The experiments show that there may be a cognitive bias toward concatenative morphology even among Arabic and Maltese speakers, but also that Arabic and Maltese speakers are willing to adjust CV skeleta and syllabic structure when deriving plural forms from singular forms. The methods that they use when producing novel plural forms are similar to those found in their L1, showing that this type of bias is predicated on morphophonological structure in the participants’ L1. The results together support a root-based lexicon for Arabic and Maltese and aggressive morphological decomposition (Boudelaa & Marslen-Wilson, 2001, 2004a, 2004b, 2015; Deutsch, Frost, & Forster, 1998; Frost, Deutsch, & Forster, 2000; Frost, Forster, & Deutsch, 1997; Ussishkin, Dawson, Wedel, & Schluter, 2015) even in novel words. Additionally, this work supports the notion of morphological abstraction, abstract grammatical features (such as past or plural) may be expressed by multiple allomorphs, particularly in the context of learning a new language. I extend this work to suggest that a processing model of Distributed Morphology (Halle & Marantz, 1993; Harley & Noyer, 1999; inter alia) would be appropriate both to model the results here and to better explain morphological processing disorders. Although Distributed Morphology has not been extensively tested as a processing model, recent research shows compatibility with existing psycholinguistic models (Gwilliams & Marantz, 2015; Stockall & Marantz, 2006) and has better explanatory power for deficits in morphological processing (Tat, 2013)

Synthetic speech vs human speech processing

Investigating whether we subconsciously process synthetic speech in the same way that we process human speech, using an auditory masked priming paradigm