How Should a Speech Recognizer Work?

Although researchers studying human speech recognition (HSR) and automatic speech recognition (ASR) share a common interest in how information processing systems (human or machine) recognize spoken language, there is little communication between the two disciplines. We suggest that this lack of communication follows largely from the fact that research in these related fields has focused on the mechanics of how speech can be recognized. In Marr's (1982) terms, emphasis has been on the algorithmic and implementational levels rather than on the computational level. In this article, we provide a computational-level analysis of the task of speech recognition, which reveals the close parallels between research concerned with HSR and ASR. We illustrate this relation by presenting a new computational model of human spoken-word recognition, built using techniques from the field of ASR that, in contrast to current existing models of HSR, recognizes words from real speech input.     

Biases of success rate differences shown in binomial effect size displays

The intent of a binomial effect size display (BESD) is to show "the [real-world] importance of [an] effect indexed by a correlation [r]" (R. Rosenthal, 1994, p. 242) by reexpressing this correlation as a success rate difference (SRD) (e.g., treatment group success rate-control group success rate). However, SRDs displayed in BESDs generally overestimate real-world SRDs implied by correlations of (a) dichotomous X and Y variables (phi coefficients), (b) dichotomous X and continuous Y variables (point-biserial coefficients [rpbs]). and (c) continuous X and Y variables (rxys). Furthermore, overestimation biases are larger for rxys than for rpbs. Differences in the sizes of biases linked to different correlations suggest that BESD SRDs reported for different correlations are not comparable. The stochastic difference index (N. Cliff, 1993: A. Vargha & H. D. Delaney, 2000) is recommended as an alternative to the BESD.     

Reducing conflicts between motor vehicles and pedestrians: the separate and combined effects of pavement markings and a sign prompt

The effects of a symbolic "yield here to pedestrians" sign and advance yield pavement markings on pedestrian/motor vehicle conflicts, motorists' yielding behavior, and the distance motorists' yield in advance of crosswalks were evaluated at multilane crosswalks at uncontrolled T intersections. In Experiment 1, the sign, when used alone, reduced pedestrian/motor vehicle conflicts and increased motorist yielding distance. The use of fluorescent yellow-green sheeting as the background of the sign did not increase the effectiveness of the sign. Further reductions in pedestrian/motor vehicle conflicts and further increases in yielding distance were associated with the addition of advance yield pavement markings. In Experiment 2, advance yield pavement markings, when used alone, were as effective in reducing pedestrian/motor vehicle conflicts and increasing yielding distance as the sign combined with pavement markings. These data suggest that the pavement markings were the essential component for reducing conflicts and increasing yielding distance.     

Neuroanatomy of the human affective system

We provide a brief overview of the structures associated with the limbic system using fixed human material. Although the review is by no means intended to be exhaustive, its purpose is to provide a tutorial on the primary structures that are involved in the experience, expression, and regulation of emotion and their anatomical location so that the reader can use this as a "pedagogical guide" for orientation and understanding of the many papers that appear in this Special Issue.     

Frontal Brain Electrical Activity in Shyness and Sociability

A number of studies have shown that shyness and sociability may be two independent personality traits that are distinguishable across a variety of measures and cultures. Utilizing recent frontal activation–emotion models as a theoretical framework, this study examined the pattern of resting frontal electroencephalographic (EEG) activity in undergraduates who self-reported high and low shyness and sociability. Analyses revealed that shyness was associated with greater relative right frontal EEG activity, whereas sociability was associated with greater relative left frontal EEG activity. Also, different combinations of shyness and sociability were distinguishable on the basis of resting frontal EEG power. Although high-shy/high-social and high-shy/low-social subjects both exhibited greater relative right frontal EEG activity, they differed significantly on EEG power in the left, but not right, frontal lead. High-shy/high-social subjects exhibited significantly less EEG power (i.e., more activity) in the left frontal lead compared with the high-shy/low-social subjects. These findings suggest that in distinguishing individual differences in personality and personality subtypes, it is important to consider not only frontal EEG asymmetry measures, but also the pattern of absolute EEG power in each frontal hemisphere.     

The Counseling Center Assessment of Psychological Symptoms Distress Index: A pragmatic exploration of general factors to enhance a multidimensional scale

Objective: The authors attempted to develop and validate a general distress index for a multidimensional psychological symptom/outcome measure used in over 300 college counseling centers with more than 100,000 cases annually: the Counseling Center Assessment of Psychological Symptoms (CCAPS). Method: Four models were compared for fit indices (n = 19,247): the existing first-order factor model (without a general factor), a second-order factor model, a bifactor model, and a single factor or “total score” model. In separate clinical and non-clinical samples, concurrent and divergent validity were examined using several well-established measures of psychological symptoms, as well as two-week test–retest and treatment utilization data. Results: Second-order and bifactor models which captured a single “distress” factor both exhibited good fit to the data relative to the baseline and “total score” model. Validity data indicated that factors adequately measured meaningful clinical onstructs. Conclusion: Both the bifactor and second-order models indicated the presence of a “distress index” comprised items across many of the CCAPS subscales. This distress scale has strong applicability for benchmarking the overall severity and complexity of patients at different centers, and can be used to help identify colleges and universities with areas of clinical strength, which can be studied to improve the field. Clinically, the distress index offers a parsimonious and efficient method for clinicians to monitor patients’ progress through treatment.