Speech Errors in the Production of Initial Consonant Clusters: The Roles of Frequency and Sonority.

PURPOSE: One of the central questions in speech production research is to what degree certain structures have an inherent difficulty and to what degree repeated encounter and practice make them easier to process. The goal of this article was to determine the extent to which frequency and sonority distance of consonant clusters predict production difficulties. METHOD: We used a tongue twister paradigm to elicit speech errors on syllable-initial German consonant clusters and investigated the relative influences of cluster frequency and sonority distance between the consonants of a cluster on production accuracy. Native speakers of German produced pairs of monosyllabic pseudowords beginning with consonant clusters at a high speech rate. RESULTS: Error rates decreased with increasing frequency of the consonant clusters. A high sonority distance, on the other hand, did not facilitate a cluster's production, but speech errors led to optimized sonority structure for a subgroup of clusters. In addition, the combination of consonant clusters in a stimulus pair has a great impact on production accuracy. CONCLUSION: These results suggest that both frequency of use and sonority distance codetermine production ease, as well as syntagmatic competition between adjacent sound sequences.

A Study of Word Complexity Under Conditions of Non-experimental, Natural Overt Speech Production Using ECoG.

The linguistic complexity of words has largely been studied on the behavioral level and in experimental settings. Only little is known about the neural processes underlying it in uninstructed, spontaneous conversations. We built up a multimodal neurolinguistic corpus composed of synchronized audio, video, and electrocorticographic (ECoG) recordings from the fronto-temporo-parietal cortex to address this phenomenon based on uninstructed, spontaneous speech production. We performed extensive linguistic annotations of the language material and calculated word complexity using several numeric parameters. We orthogonalized the parameters with the help of a linear regression model. Then, we correlated the spectral components of neural activity with the individual linguistic parameters and with the residuals of the linear regression model, and compared the results. The proportional relation between the number of consonants and vowels, which was the most informative parameter with regard to the neural representation of word complexity, showed effects in two areas: the frontal one was at the junction of the premotor cortex, the prefrontal cortex, and Brodmann area 44. The postcentral one lay directly above the lateral sulcus and comprised the ventral central sulcus, the parietal operculum and the adjacent inferior parietal cortex. Beyond the physiological findings summarized here, our methods may be useful for those interested in ways of studying neural effects related to natural language production and in surmounting the intrinsic problem of collinearity between multiple features of spontaneously spoken material.

Real-life speech production and perception have a shared premotor-cortical substrate.

Motor-cognitive accounts assume that the articulatory cortex is involved in language comprehension, but previous studies may have observed such an involvement as an artefact of experimental procedures. Here, we employed electrocorticography (ECoG) during natural, non-experimental behavior combined with electrocortical stimulation mapping to study the neural basis of real-life human verbal communication. We took advantage of ECoG's ability to capture high-gamma activity (70-350 Hz) as a spatially and temporally precise index of cortical activation during unconstrained, naturalistic speech production and perception conditions. Our findings show that an electrostimulation-defined mouth motor region located in the superior ventral premotor cortex is consistently activated during both conditions. This region became active early relative to the onset of speech production and was recruited during speech perception regardless of acoustic background noise. Our study thus pinpoints a shared ventral premotor substrate for real-life speech production and perception with its basic properties.

[Psychosomatics in gastroenterology - statement of the Work Group for Psychosomatics in Gastroenterology of the German Society of Gastroenterology, Digestive and Metabolic Diseases (DGVS)]. / Psychosomatik in der Gastroenterologie ­ Stellungnahme der Arbeitsgemeinschaft Psychosomatik in der Gastroenterologie der Deutschen Gesellschaft für Gastroenterologie, Verdauungs- und Stoffwechselkrankheiten (DGVS).

The Association Psychosomatics in Gastroenterology of the DGVS aims to sharpen the profile of psychosomatic proportions in diagnostics, differential diagnostics and therapy of gastroenterological diseases, increasingly establish psychosomatic aspects in further education and clinical practice guidelines, deepen the cooperation with psychosomatic societies and strengthen the job satisfaction and mental health of gastroenterologists in Germany.

Medically unexplained symptoms as a threat to patients' identity? A conversation analysis of patients' reactions to psychosomatic attributions.

OBJECTIVE: Interactions between patients suffering from medically unexplained symptoms (MUS) and their physicians are usually perceived as difficult and unsatisfactory by both parties. In this qualitative study, patients' reactions to psychosomatic attributions were analyzed on a micro-level. METHODS: 144 consultations between consultation-and-liaison (CL) psychotherapists and inpatients with MUS, who were treated according to a modified reattribution model, were recorded. Linguists and psychologists evaluated these consultations by applying conversation and positioning analysis. RESULTS: When introducing a psychosomatic attribution, therapists use discursive strategies to exert interactional pressure on the patient; while simultaneously using careful and implicit formulations. Three linguistic patterns could be found in which patients subtly refute, drop or undermine the psychosomatic attribution in their reply. Moreover, in this context patients position themselves as somatically ill or justify their own life situation. CONCLUSION: The results suggest that patients interpret psychosomatic attributions and even subtle suggestions from the psychotherapists as face-threatening 'other-positionings'. PRACTICE IMPLICATIONS: When implementing the reattribution model, it should be taken into account that interactional resistance might be a necessary step in the process of the patient's understanding. Nevertheless therapists should introduce reattribution in a patient-centered rather than persuasive way and they should openly address patients' fears of being stigmatized.

A learning rule for very simple universal approximators consisting of a single layer of perceptrons.

One may argue that the simplest type of neural networks beyond a single perceptron is an array of several perceptrons in parallel. In spite of their simplicity, such circuits can compute any Boolean function if one views the majority of the binary perceptron outputs as the binary output of the parallel perceptron, and they are universal approximators for arbitrary continuous functions with values in [0,1] if one views the fraction of perceptrons that output 1 as the analog output of the parallel perceptron. Note that in contrast to the familiar model of a "multi-layer perceptron" the parallel perceptron that we consider here has just binary values as outputs of gates on the hidden layer. For a long time one has thought that there exists no competitive learning algorithm for these extremely simple neural networks, which also came to be known as committee machines. It is commonly assumed that one has to replace the hard threshold gates on the hidden layer by sigmoidal gates (or RBF-gates) and that one has to tune the weights on at least two successive layers in order to achieve satisfactory learning results for any class of neural networks that yield universal approximators. We show that this assumption is not true, by exhibiting a simple learning algorithm for parallel perceptrons - the parallel delta rule (p-delta rule). In contrast to backprop for multi-layer perceptrons, the p-delta rule only has to tune a single layer of weights, and it does not require the computation and communication of analog values with high precision. Reduced communication also distinguishes our new learning rule from other learning rules for parallel perceptrons such as MADALINE. Obviously these features make the p-delta rule attractive as a biologically more realistic alternative to backprop in biological neural circuits, but also for implementations in special purpose hardware. We show that the p-delta rule also implements gradient descent-with regard to a suitable error measure-although it does not require to compute derivatives. Furthermore it is shown through experiments on common real-world benchmark datasets that its performance is competitive with that of other learning approaches from neural networks and machine learning. It has recently been shown [Anthony, M. (2007). On the generalization error of fixed combinations of classifiers. Journal of Computer and System Sciences 73(5), 725-734; Anthony, M. (2004). On learning a function of perceptrons. In Proceedings of the 2004 IEEE international joint conference on neural networks (pp. 967-972): Vol. 2] that one can also prove quite satisfactory bounds for the generalization error of this new learning rule.

Generic object recognition with boosting.

This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of either discontinuity or homogeneity. A variety of local descriptors can be applied to form a set of feature vectors for each local region. Boosting is used to learn a subset of such feature vectors (weak hypotheses) and to combine them into one final hypothesis for each visual category. This combination of individual extractors and descriptors leads to recognition rates that are superior to other approaches which use only one specific extractor/descriptor setting. To explore the limitation of our system, we had to set up new, highly complex image databases that show the objects of interest at varying scales and poses, in cluttered background, and under considerable occlusion. We obtain classification results up to 81 percent ROC-equal error rate on the most complex of our databases. Our approach outperforms all comparable solutions on common databases.

Identification of regional varieties by intonational cues. An experimental study on Hamburg and Berlin German.

Two experiments examined the commonly held belief that regional varieties of German can be identified by intonational features alone. In both experiments, listeners were presented with regional intonational contours of German. In the first experiment, listeners judged contours of Hamburg urban vernacular compared with contours of Northern Standard German. In the second experiment, listeners judged contours of Berlin urban vernacular compared with contours of both Northern Standard German and Low Alemannic German. The performance of listeners was found to vary with their linguistic experience. Listeners who were familiar both with the local variety and with some nonlocal variety by personal contact performed better than listeners who were familiar with the local variety only. Moreover, also listeners not familiar with Hamburg German and Berlin German, respectively, were found to perform the identification test with some success. This led to the conclusion that overall success rates do not only depend on true recognition of local contours but may additionally be enhanced by using some kind of elimination strategy. A second factor that affected performance was the choice of speaker for generating the carrier utterances. In the first experiment, all carrier utterances were produced by a speaker of Northern Standard German. In the second experiment, two sets of carrier utterances were used. The first set was obtained from a speaker of Northern Standard German and the second set from a speaker of Berlin urban vernacular. As expected, Berlin contours were better identified when presented with an utterance that was produced by a speaker of Berlin urban vernacular. However, no uniform effect was found for the different contours that were examined.