Evaluating models of working memory: FMRI and behavioral evidence on the effects of concurrent irrelevant information

FMRI and behavioral methods were used to examine working memory impairments resulting from articulatory suppression, irrelevant speech, and irrelevant nonspeech. While the deleterious effects of these three irrelevant information types are well established in the behavioral literature, theoretical models provide conflicting accounts of the origins of these effects. To adjudicate between these accounts, two experiments were conducted. Experiment 1 examined fMRI signal changes in a delayed probed recall task with articulatory suppression, irrelevant speech, or irrelevant nonspeech imposed during the encoding and delay periods. Within the principally frontal and left-lateralized network of brain regions engaged by the task, articulatory suppression caused a relative increase in activity early in the trial, while both irrelevant speech and nonspeech conditions caused relative reductions in regional activity later in the trial. In a subsequent behavioral experiment (Experiment 2), the specific timing of interference was manipulated to further explore apparent differences in the temporal specificity of the effects. Subjects performed a delayed serial recall task while irrelevant information was imposed during specific trial stages: encoding, delay, or recall. Articulatory suppression was found to be most effectual when it coincided with item encoding, while both irrelevant speech and irrelevant nonspeech were most effectual when presented during the post-presentation delay. Taken together, these experiments provide convergent evidence for a dissociation of articulatory suppression from the two irrelevant sound conditions, but suggest that the effects of irrelevant speech and irrelevant nonspeech are functionally equivalent. This pattern of dissociation is predicted by the Embedded-Processes model (Cowan, 1995), but proves challenging to explain in the context of alternative theories

Articulatory characteristics of sibilant production in young people with Down's syndrome

Speech production in children with Down’s syndrome (DS) has been found to be variable and inconsistent. Errors are concentrated in consonants that are typically late developing, such as fricatives. It has been suggested that inconsistency in speech production in DS is a result of a motor speech deficit but there is little detailed articulatory evidence to support this claim. This study (with data from MRC grant ‘Assessment and Treatment of Impaired Speech Motor Control in Children with Down's syndrome’ (G0401388)) provides a detailed phonetic analysis of the voiceless sibilants /s/ and /ʃ/, in a group of young people with DS, by means of auditory and articulatory analysis. The aim of the study is to assess fine motor ability and articulation variability at word level production in a group of speakers with well-established difficulties in speech articulation. The study analysed data from 25 children with DS, 10 typically developing children and 8 adult speakers, recorded using EPG. Perceptual measures were compared with quantitative analyses of EPG data, along with visual analysis of articulation patterns based on a new set of articulation taxonomies. The data is presented by group and in the form of 5 case studies. The case studies provide a means to analyse the relationship between articulation and auditory information in detail and to compare these with supplementary motor control measures. The results show presence of atypical articulation patterns for speakers with DS for both perceptually acceptable tokens, and those in error. Higher levels of within-speaker articulation variability are presented in comparison to the TD control group. Further findings suggest presence of articulation patterns in the TD speakers previously unidentified in EPG studies. Similar to previous studies, the results find that speakers with DS are a highly variable group and that speakers display a combination of typical and atypical speech patterns, influenced by speech motor control difficulties.sub_shsunpub2190_ethesesunpu

An exploration of the rhythm of Malay

In recent years there has been a surge of interest in speech rhythm. However we still lack a clear understanding of the nature of rhythm and rhythmic differences across languages. Various metrics have been proposed as means for measuring rhythm on the phonetic level and making typological comparisons between languages (Ramus et al, 1999; Grabe & Low, 2002; Dellwo, 2006) but the debate is ongoing on the extent to which these metrics capture the rhythmic basis of speech (Arvaniti, 2009; Fletcher, in press). Furthermore, cross linguistic studies of rhythm have covered a relatively small number of languages and research on previously unclassified languages is necessary to fully develop the typology of rhythm. This study examines the rhythmic features of Malay, for which, to date, relatively little work has been carried out on aspects rhythm and timing. The material for the analysis comprised 10 sentences produced by 20 speakers of standard Malay (10 males and 10 females). The recordings were first analysed using rhythm metrics proposed by Ramus et. al (1999) and Grabe & Low (2002). These metrics (∆C, %V, rPVI, nPVI) are based on durational measurements of vocalic and consonantal intervals. The results indicated that Malay clustered with other so-called syllable-timed languages like French and Spanish on the basis of all metrics. However, underlying the overall findings for these metrics there was a large degree of variability in values across speakers and sentences, with some speakers having values in the range typical of stressed-timed languages like English. Further analysis has been carried out in light of Fletcher’s (in press) argument that measurements based on duration do not wholly reflect speech rhythm as there are many other factors that can influence values of consonantal and vocalic intervals, and Arvaniti’s (2009) suggestion that other features of speech should also be considered in description of rhythm to discover what contributes to listeners’ perception of regularity. Spectrographic analysis of the Malay recordings brought to light two parameters that displayed consistency and regularity for all speakers and sentences: the duration of individual vowels and the duration of intervals between intensity minima. This poster presents the results of these investigations and points to connections between the features which seem to be consistently regulated in the timing of Malay connected speech and aspects of Malay phonology. The results are discussed in light of current debate on the descriptions of rhythm

A Neurocomputational Model of Grounded Language Comprehension and Production at the Sentence Level

While symbolic and statistical approaches to natural language processing have become undeniably impressive in recent years, such systems still display a tendency to make errors that are inscrutable to human onlookers. This disconnect with human processing may stem from the vast differences in the substrates that underly natural language processing in artificial systems versus biological systems. To create a more relatable system, this dissertation turns to the more biologically inspired substrate of neural networks, describing the design and implementation of a model that learns to comprehend and produce language at the sentence level. The model's task is to ground simulated speech streams, representing a simple subset of English, in terms of a virtual environment. The model learns to understand and answer full-sentence questions about the environment by mimicking the speech stream of another speaker, much as a human language learner would. It is the only known neural model to date that can learn to map natural language questions to full-sentence natural language answers, where both question and answer are represented sublexically as phoneme sequences. The model addresses important points for which most other models, neural and otherwise, fail to account. First, the model learns to ground its linguistic knowledge using human-like sensory representations, gaining language understanding at a deeper level than that of syntactic structure. Second, analysis provides evidence that the model learns combinatorial internal representations, thus gaining the compositionality of symbolic approaches to cognition, which is vital for computationally efficient encoding and decoding of meaning. The model does this while retaining the fully distributed representations characteristic of neural networks, providing the resistance to damage and graceful degradation that are generally lacking in symbolic and statistical approaches. Finally, the model learns via direct imitation of another speaker, allowing it to emulate human processing with greater fidelity, thus increasing the relatability of its behavior. Along the way, this dissertation develops a novel training algorithm that, for the first time, requires only local computations to train arbitrary second-order recurrent neural networks. This algorithm is evaluated on its overall efficacy, biological feasibility, and ability to reproduce peculiarities of human learning such as age-correlated effects in second language acquisition