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Current models of spoken word recognition have been predominantly based on studies of Indo-European languages. As a result, little is known about the recognition processes involved in the perception of tonal languages (e.g., Mandarin Chinese), and the role of lexical tone in speech perception. One view is that tonal languages are processed phonologically through individual segments, while another view is that they are processed lexically as a whole. Moreover, a recent study claimed to be the first to discover an early phonological processing stage in Mandarin (Huang et al., 2014). There seems to be a lack of investigations concerning tonal languages, as no clear conclusions have been made about the nature of tonal processes, or a model of spoken word recognition that best incorporates lexical tone. The current study addressed these issues by presenting 18 native Mandarin speakers with aural sentences with medial target words, which either matched or mismatched the preceding visually presented sentences with medial target words (e.g, 家 /jia1/ “home”). Violation conditions involved target words that differed in the following ways: tone violation, where only the tone was different (e.g., 价 /jia4/ “price”), onset violation, where only the onset was different (e.g., 虾 /xia1/ “shrimp”), and syllable violation, where both the tone and the onset were different (e.g., 糖 /tang2/ “candy”). We did not find evidence for an early phonological processing stage in Mandarin. Instead, our findings indicate that Mandarin syllables are processed incrementally through phonological segments and that lexical tone is strongly associated with semantic access. These results are discussed with respect to modifications for existing models in spoken word recognition to incorporate the processes involved with tonal language recognition. / Thesis / Master of Science (MSc)

In the last decades, computational models have become useful tools for studying biological neural networks. These models are typically constrained by either behavioural data from neuropsychological studies or by biological data from neuroscience. One model of the latter kind is the Bayesian Confidence Propagating Neural Network (BCPNN) - an attractor network with a Bayesian learning rule which has been proposed as a model for various types of memory. In this thesis, I have further studied the potential of the BCPNN in short-term sequential memory. More specifically, I have investigated if the network can be used to qualitatively replicate behaviours of immediate verbal serial recall, and thereby offer insight into the network-level mechanisms which give rise to these behaviours. The simulations showed that the model was able to reproduce various benchmark effects such as the word length and irrelevant speech effects. It could also simulate the bow shaped positional accuracy curve as well as some backward recall if the to-be recalled sequence was short enough. Finally, the model showed some ability to handle sequences with repeated patterns. However, the current model architecture was not sufficient for simulating the effects of rhythm such as temporally grouping the inputs or stressing a specific element in the sequence. Overall, even though the model is not complete, it showed promising results as a tool for investigating biological memory and it could explain various benchmark behaviours in immediate serial recall through neuroscientifically inspired learning rules and architecture. / Under de senaste årtionden har datorsimulationer blivit ett allt mer populärt verktyg för att undersöka biologiska neurala nätverk. Dessa modeller är vanligtvis inspirerade av antingen beteendedata från neuropsykologiska studier eller av biologisk data från neurovetenskapen. En modell av den senare typen är ett Bayesian Confidence Propagating Neural Network (BCPNN) - ett autoassociativt nätverk med en Bayesiansk inlärningsregel, vilket tidigare har använts för att modellera flera typer av minne. I det här examensarbetet har jag vidare undersökt om nätverket kan användas som en modell för sekventiellt korttidsminne genom att undersöka dess förmåga att replikera beteenden inom verbalt sekventiellt korttidsminne. Experimenten visade att modellen kunde simulera ett flertal viktiga nyckeleffekter såsom the word length effect och the irrelevant speech effect. Däröver kunde modellen även simulera den bågformade kurvan som beskriver andelen lyckade repetitioner som en funktion av position, och den kunde dessutom repetera korta sekvenser baklänges. Modellen visade också på viss förmåga att hantera sekvenser där ett element återkom senare i sekvensen. Den nuvarande modellen var däremot inte tillräcklig för att simulera effekterna som tillkommer av rytm, såsom temporär gruppering eller en betoning på specifika element i sekvensen. I sin helhet ser modellen däremot lovande ut, även om den inte är fullständig i sin nuvarande form, då den kunde simulera ett flertal viktiga nyckeleffekter och förklara dessa med hjälp av neurovetenskapligt inspirerade inlärningsregler.

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Thesis (M.A. (Translation Studies and Linguistics)) -- University of Limpopo, 2022 / The aim of this study was to examine the morpho-phonological properties of the anaphoric constructions in Northern Sotho using Binding Theory. This study adopted the qualitative research method, where participant observation was used to collect data. The study employed Textual Analysis to analyse the data. The study identified reflexive and reciprocal data that constitute anaphors in Northern Sotho. The study’s findings indicate that there are two types of anaphors, namely: reciprocals and reflexives. In Northern Sotho, anaphors are in the form of verbs. The basic structure of the reciprocal is the root verb, the reciprocal suffix (-an) plus the terminative vowel (-a). The study found that reciprocals do not change or influence the phonology of the verb. Yet another finding is that reflexives change the phonology of the verb. When the reflexive prefix -i is attached to the root verb, it sometimes changes the assimilation process.