Expressing intent, imminence and ire by attributing speech/thought in Mongolian

Quoted clauses in which an intention is declared are cross-linguistically known to develop into clauses that directly ascribe an intention to their subjects, and further into clauses that express the imminence of an event. In Khalkha Mongolian, several quotative constructions based on the quotative verb ge- have come to ascribe intention and then developed further semantic extensions: (i) The pattern -x ge-, featuring a fossilized Middle Mongol future-referring participial suffix, is used in a group of constructions that cover the semantic space between future time reference, intention (initially of the current speaker), and imminence. (ii) Quotational clauses ending in a particular tense-aspect-evidentiality suffix (including -n) and subordinated by a linking converb ge-ž/ge-ed are often systematically ambiguous between quotation and their purposive, causal and concessive extensions. Noun phrases with similar properties additionally allow for (dedicational-)benefactive and (allocational-)functive uses. (iii) The pattern -n ge-, which in other Central Mongolic varieties resembles -x ge-, conveys the speaker’s disbelief and anger about an actor’s willful deeds when used in echo questions marked by -n=AA. Based on conversational corpus data, this paper tries to provide a comprehensive picture of Khalkha Mongolian constructions in which the speaker’s awareness of the subject’s speech or thoughts is reinterpreted as attributing intentions and their derived notions

Beyond the screen – The potential of smartphone apps and immersive technologies in exposure-based interventions for phobias

Specific phobias are extremely common among adults. They are characterized by strong emotional reactions and avoidance behavior when exposed to the feared stimuli. Specifically fears concerning heights or animals such as spiders are highly prevalent, followed by fear of social situations such as fear of public speaking. The gold standard in treating specific phobias is exposure-based therapy. However, exposure-based therapy is limited in its practicability in clinical routine and poses a high hurdle for affected individuals. Virtual and augmented reality (VR/AR) smartphone apps offer attractive platforms to simulate exposure situations and by that increase the accessibility of mental health services in general. Thus, novel smartphone-based treatments hold the potential to facilitate the dissemination of exposure-based treatments for specific phobias. The studies presented as part of this thesis aimed at investigating three newly developed interventions for fear of heights, fear of public speaking and fear of spiders, using the currently available advanced technologies. In the first study (Bentz et al., 2021), a stand-alone, automated and gamified VR exposure app Easyheights was developed using 360° images. The app’s effectiveness to reduce fear of heights and avoidance behavior was investigated in a randomized controlled trial in an adult population with clinical and subclinical fear of heights. The repeated use of the app led to reduced fear and avoidance behavior in a real-life situation on a tower. For the second study (Müller, Fehlmann et al., 2022), the developed stand-alone, automated and gamified VR exposure app Fearless Speech aimed at reducing public speaking anxiety (PSA) and avoidance of eye contact. A virtual audience with 360° videos was used for the exposure and gaze control for the eye contact training. The app was investigated in a randomized controlled trial in healthy adults with subclinical PSA. After the repeated use of the app, participants showed reduced fear and improved eye contact in a real-life speech situation. The third study (Zimmer et al., 2021) examined the developed stand-alone, automated and gamified AR exposure app Phobys. In comparison to VR, AR has only recently been introduced to clinical research. The app was designed to reduce fear, disgust and avoidance behavior in adults with clinical and subclinical fear of spiders. The results of the randomized controlled trial showed that repeatedly using the app led to reduced fear, disgust and avoidance behavior in a real-life situation with a real spider. The results of these studies support the potential of stand-alone, automated VR and AR interventions delivered through smartphone apps. The developed apps allow for a high-quality user experience with a highly realistic environment, gaze control for an easy navigation as well as the possibility of interaction. In addition, gamification elements foster engagement with the apps. All three investigated apps offer low-threshold and low-cost treatment for individuals affected by specific phobias. Testing the effectiveness of these newly developed apps in real-life settings sets them apart from previous studies. Hence, this thesis highlights the potential of using smartphone apps with immersive technologies to advance and disseminate exposure-based treatments for specific phobias

Integrating Gestures

Gestures convey information about culture, discourse, thought, intentionality, emotion, intersubjectivity, cognition, and first and second language acquisition. Additionally, they are used by non-human primates to communicate with their peers and with humans. Consequently, the modern field of gesture studies has attracted researchers from a number of different disciplines such as anthropology, cognitive science, communication, neuroscience, psycholinguistics, primatology, psychology, robotics, sociology and semiotics. This volume presents an overview of the depth and breadth of current research in gesture. Its focus is on the interdisciplinary nature of gesture. The chapters included in the volume are divided into six themes: the nature and functions of gesture, first language development and gesture, second language effects on gesture, gesture in the classroom and in problem solving, gesture aspects of discourse and interaction, and gestural analysis of music and dance

KEER2022

Avanttítol: KEER2022. DiversitiesDescripció del recurs: 25 juliol 202

Towards the Development of an IsiXhosa Adaptation of the MacArthur-Bates Communicative Development Inventory for Toddlers

In this thesis, I draw on experiences of the isiXhosa segment of the pre-pilot research phase and first rural, toddler pilot for the adaptation of the MacArthur-Bates Communicative Development Inventory (CDI) into Southern African languages. 1 The adaptation stems from the growing dissatisfaction regarding the dearth of speech and language assessments and therapeutic tools currently available in South Africa for isiXhosa or other local languages (Pascoe and Smouse, 2012; Demuth, 2007). Such tools are of fundamental importance since failure to accurately diagnose communication difficulties hinders appropriate intervention. If improperly addressed, communication difficulties can hamper the essential development of literacy skills and academic success (see Shonkoff and Phillips, 2000). Reliable research on child language acquisition is thus critically needed in order to inform culturally and linguistically appropriate assessments that can lead to accurate diagnosis and treatment of communication disorders, and ultimately improve children’s early childhood development trajectories. Data from the pre-pilot and pilot study informs discussions about monolingual isiXhosa-speaking toddlers’ lexical and grammatical acquisition. I furthermore discuss the need for the adaptation of such inventories to local circumstances, and I problematise the assumption that Western linguistic constructs, ontologies, and epistemologies are appropriate for the CDI exercise as applied to Bantu languages. The findings of this study furthermore contribute to existing scholarship on how children acquire words and morphemes. Findings as such will be of use to clinicians and speech pathologists, especially in informing vital language and communication rehabilitation in early childhood development. I additionally hope that the results presented will inform cross-linguistic scholarship on child language acquisition, paving the way for future research as well as the creation of bi- and multilingual CDIs

Understanding and Supporting Vocabulary Learners via Machine Learning on Behavioral and Linguistic Data

This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized features for the system. The first study presents how behavioral and linguistic interactions from the vocabulary tutoring system can be used to predict students' off-task states. The study identifies which predictive features from interaction signals are more important and examines different types of off-task behaviors. The second study investigates how to automatically evaluate students' partial word knowledge from open-ended responses to definition questions. We present a technique that augments modern word-embedding techniques with a classic semantic differential scaling method from cognitive psychology. We then use this interpretable semantic scale method for predicting students' short- and long-term learning. The third and fourth studies show how to develop a model that can generate more efficient training curricula for both human and machine vocabulary learners. The third study illustrates a deep-learning model to score sentences for a contextual vocabulary learning curriculum. We use pre-trained language models, such as ELMo or BERT, and an additional attention layer to capture how the context words are less or more important with respect to the meaning of the target word. The fourth study examines how the contextual informativeness model, originally designed to develop curricula for human vocabulary learning, can also be used for developing curricula for various word embedding models. We identify sentences predicted as low informative for human learners are also less helpful for machine learning algorithms. Having a rich understanding of user behaviors, responses, and learning stimuli is imperative to develop an intelligent online system. Our studies demonstrate interpretable methods with cross-disciplinary approaches to understand various cognitive states of students during learning. The analysis results provide data-driven evidence for designing personalized features that can maximize learning outcomes. Datasets we collected from the studies will be shared publicly to promote future studies related to online tutoring systems. And these findings can also be applied to represent different user states observed in other online systems. In the future, we believe our findings can help to implement a more personalized vocabulary learning system, to develop a system that uses non-English texts or different types of inputs, and to investigate how the machine learning outputs interact with students.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162999/1/sjnam_1.pd

Autoimmune Epilepsy in Childhood

The role of immune mediated mechanisms is increasingly recognised in patients with seizures and epilepsies. Recently the term "autoimmune epilepsy" has been used to imply involvement of the adaptive immune system (particularly humoral) in the pathogenesis of epilepsy. Specific neuronal antibodies against cell surface proteins as well as some intracellular antigens are now recognised in a proportion of adult patients with seizures. The seizures are often severe and not isolated, but rather accompanied by encephalopathy or other neurologic symptoms. Evidence of brain inflammation might be found in cerebrospinal fluid or imaging. The best recognised disorders are limbic encephalitis (associated with antibodies against many neuronal antigens such as VGKC-complex proteins and GAD), and NMDAR encephalitis. However neuronal antibodies are also found in some adult patients with seizures and epilepsies in the absence of encephalopathy or other features. My PhD project aimed to study and investigate neuronal antibodies in children with seizures. This study hoped to help identify children who may have ‘autoimmune seizures and epilepsies’. The studies conducted as part of this thesis found VGKC-complex antibodies in 4 of 10 patients with unexplained encephalitis. Furthermore neuronal antibodies were found in 11 of 114 children with new onset seizures mainly those with epilepsy of unknown cause (predominantly focal). Neuronal antibodies were also found in 7 of 13 patients who had suspected autoimmune epilepsy. The findings in these studies are novel and have shed some light into the importance of neuronal antibodies in paediatric seizures. While the pathogenic role of these antibodies remains a hot topic for debates and future studies, we think that the presence of these antibodies define a group of patients where immune mechanisms are important, and where immunotherapy might improve the clinical outcome