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This project describes the nominal, verbal and ‘truncation’ systems of Awing and explains the syntactic and semantic functions of the multifunctional l<-><-> (LE) morpheme in copular and wh-focused constructions. Awing is a Bantu Grassfields language spoken in the North West region of Cameroon. The work begins with morphological processes viz. deverbals, compounding, reduplication, borrowing and a thorough presentation of the pronominal system and takes on verbal categories viz. tense, aspect, mood, verbal extensions, negation, adverbs and triggers of a homorganic N(asal)-prefix that attaches to the verb and other verbal categories. Awing grammar also has a very unusual phenomenon whereby nouns and verbs take long and short forms. A chapter entitled truncation is dedicated to the phenomenon. It is observed that the truncation process does not apply to bare singular NPs, proper names and nouns derived via morphological processes. On the other hand, with the exception of the 1st person non-emphatic possessive determiner and the class 7 noun prefix, nouns generally take the truncated form with modifiers (i.e., articles, demonstratives and other possessives). It is concluded that nominal truncation depicts movement within the DP system (Abney 1987). Truncation of the verb occurs in three contexts: a mass/plurality conspiracy (or lattice structuring in terms of Link 1983) between the verb and its internal argument (i.e., direct object); a means to align (exhaustive) focus (in terms of Fery’s 2013), and a means to form polar questions.
The second part of the work focuses on the role of the LE morpheme in copular and wh-focused clauses. Firstly, the syntax of the Awing copular clause is presented and it is shown that copular clauses in Awing have ‘subject-focus’ vs ‘topic-focus’ partitions and that the LE morpheme indirectly relates such functions. Semantically, it is shown that LE does not express contrast or exhaustivity in copular clauses. Turning to wh-constructions, the work adheres to Hamblin’s (1973) idea that the meaning of a question is the set of its possible answers and based on Rooth’s (1985) underspecified semantic notion of alternative focus, concludes that the LE morpheme is not a Focus Marker (FM) in Awing: LE does not generate or indicate the presence of alternatives (Krifka 2007); The LE morpheme can associate with wh-elements as a focus-sensitive operator with semantic import that operates on the focus alternatives by presupposing an exhaustive answer, among other notions. With focalized categories, the project further substantiates the claim in Fominyam & Šimík (2017), namely that exhaustivity is part of the semantics of the LE morpheme and not derived via contextual implicature, via a number of diagnostics. Hence, unlike in copular clauses, the LE morpheme with wh-focused categories is analysed as a morphological exponent of a functional head Exh corresponding to Horvath's (2010) EI (Exhaustive Identification). The work ends with the syntax of verb focus and negation and modifies the idea in Fominyam & Šimík (2017), namely that the focalized verb that associates with the exhaustive (LE) particle is a lower copy of the finite verb that has been moved to Agr. It is argued that the LE-focused verb ‘cluster’ is an instantiation of adjunction. The conclusion is that verb doubling with verb focus in Awing is neither a realization of two copies of one and the same verb (Fominyam and Šimík 2017), nor a result of a copy triggered by a focus marker (Aboh and Dyakonova 2009). Rather, the focalized copy is said to be merged directly as the complement of LE forming a type of adjoining cluster.
Argument mining on twitter
(2021)
In the last decade, the field of argument mining has grown notably. However, only relatively few studies have investigated argumentation in social media and specifically on Twitter. Here, we provide the, to our knowledge, first critical in-depth survey of the state of the art in tweet-based argument mining. We discuss approaches to modelling the structure of arguments in the context of tweet corpus annotation, and we review current progress in the task of detecting argument components and their relations in tweets. We also survey the intersection of argument mining and stance detection, before we conclude with an outlook.
In successful communication, the literal meaning of linguistic utterances is often enriched by pragmatic inferences. Part of the pragmatic reasoning underlying such inferences has been successfully modeled as Bayesian goal recognition in the Rational Speech Act (RSA) framework. In this paper, we try to model the interpretation of question-answer sequences with narrow focus in the answer in the RSA framework, thereby exploring the effects of domain size and prior probabilities on interpretation. Should narrow focus exhaustivity inferences be actually based on Bayesian inference involving prior probabilities of states, RSA models should predict a dependency of exhaustivity on these factors. We present experimental data that suggest that interlocutors do not act according to the predictions of the RSA model and that exhaustivity is in fact approximately constant across different domain sizes and priors. The results constitute a conceptual challenge for Bayesian accounts of the underlying pragmatic inferences.
Apples and oranges
(2021)
Despite scarce empirical evidence, introducing new vocabulary in semantic categories has long been standard in second language teaching. We examined the effect of learning context on encoding, immediate recall and integration of new vocabulary into semantic memory by contrasting categorically related (novel names for familiar concepts blocked by semantic category) and unrelated (mixed semantic categories) learning contexts. Two learning sessions were conducted 24 hours apart, with each participant exposed to both contexts. Subsequently, a test phase examined picture naming, translation and picture-word interference tasks. Compared to the unrelated context, the categorically related context resulted in poorer naming accuracy in the learning phase, slower response latencies at the immediate recall tasks and greater semantic interference in the picture-word interference task (picture naming in L1 with semantically related novel word distractors). We develop a theoretical account of word learning that attributes observed differences to episodic rather than semantic memory.
Advocating the inclusion of older adults in digital language learning technology and research
(2021)
In eye-movement control during reading, advanced process-oriented models have been developed to reproduce behavioral data. So far, model complexity and large numbers of model parameters prevented rigorous statistical inference and modeling of interindividual differences. Here we propose a Bayesian approach to both problems for one representative computational model of sentence reading (SWIFT; Engbert et al., Psychological Review, 112, 2005, pp. 777-813). We used experimental data from 36 subjects who read the text in a normal and one of four manipulated text layouts (e.g., mirrored and scrambled letters). The SWIFT model was fitted to subjects and experimental conditions individually to investigate between- subject variability. Based on posterior distributions of model parameters, fixation probabilities and durations are reliably recovered from simulated data and reproduced for withheld empirical data, at both the experimental condition and subject levels. A subsequent statistical analysis of model parameters across reading conditions generates model-driven explanations for observable effects between conditions.