Speech articulation in children with Williams syndrome or 7q11.23 duplication syndrome.

Williams syndrome (WS) and 7q11.23 duplication syndrome (Dup7) are associated with communication disorders (Huffman et al., 2013). However, articulatory accuracy has not been systematically examined in these populations. The dissertation involved two studies. Using standardized citation assessment, Study 1 addressed articulatory accuracy with regard to age norms and differences between groups. Results indicated that for both groups, (a) consonant accuracy was significantly below expectations, (b) older children pronounced consonants with significantly better accuracy than younger children, (c) children with IQs at or above 70 earned significantly higher articulation standard scores, and (d) for particular groups of consonant sounds, arranged as a function of features of articulation, significant differences were found across consonant groups for (c.1) expected period of acquisition in development, (c.2) articulatory place of production, (c.3) articulatory manner of production, and (c.4) movement transition across consonants within clusters. Study 2 addressed variance relations among speech articulatory accuracy, phonological processing, and particular cognitive and linguistic measures. Articulatory accuracy was shown moderately, to strongly, related to each study variable. For the children with WS, articulatory accuracy contributed unique variance to phonological processing beyond that contributed by verbal short-term memory, spatial ability, and the combined factor of lexical understanding and use. Overall, the results showed children in both groups were significant delayed in consonantal development. Patterns of articulatory accuracy did not differ greatly from those of younger, typically developing children. Furthermore, the findings demonstrated positive relations among articulatory accuracy, phonological processing, intellectual abilities, and vocabulary abilities for children with these syndromes

Paralinguistic and Nonverbal Behaviour in Social Interactions: A Lens Model Perspective

It is widely accepted in our society that people’s paralinguistic (i.e., non-semantic characteristics of the voice) and nonverbal (i.e., posture, gestures, and facial expressions) behaviours play an important role in conveying information about their personality traits. Two particularly relevant traits include one’s preferred levels of dominance and affiliation, which are the two major axes of the interpersonal circumplex. The current study investigates how dominance and affiliation are conveyed through paralinguistic and nonverbal behaviour using a lens model framework. Two major issues addressed by this framework include: 1) How do observers make inferences about people’s dominance and affiliation using paralinguistic and nonverbal behaviours and 2) How do people’s trait dominance and affiliation relate to these behavioural cues? To examine these two questions, we collected data from 114 opposite-sex dyads who worked together to complete a relatively unstructured collaborative task. The videotaped interactions were coded for specific paralinguistic (e.g., pitch, volume, resonance) and nonverbal (e.g., hand gestures, trunk posture, facial expressions) behaviours, in addition to coding more global displays of dominance and affiliation. Participants also completed several measures of trait dominance and affiliation, which tapped both their relatively conscious (i.e., explicit) and their relatively unconscious (i.e., implicit) levels of these traits. Our findings suggest that observers used mainly paralinguistic behaviour to infer dominance and mainly nonverbal behaviour to infer affiliation. In comparison to observers’ perceptions, there were fewer significant relations between individuals’ self-reported trait dominance and affiliation and the nonverbal and paralinguistic behaviours they expressed during the interaction, suggesting that people may have limited conscious awareness of how these behaviours convey information about their trait dominance and affiliation. In line with this idea, several behaviours showed relations to implicit measures of trait dominance and affiliation. We also conducted factor analyses of the measured paralinguistic and nonverbal behaviours, to examine whether or not these behaviours might co-occur as subsets or factors. We found that paralinguistic and nonverbal behaviours can be captured by overarching factors which relate meaningfully to measures of dominance and affiliation. Finally, we demonstrated that dyad members’ paralinguistic and nonverbal behaviours become interdependent as they interact with one another

Models and analysis of vocal emissions for biomedical applications: 5th International Workshop: December 13-15, 2007, Firenze, Italy

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies. The Workshop has the sponsorship of: Ente Cassa Risparmio di Firenze, COST Action 2103, Biomedical Signal Processing and Control Journal (Elsevier Eds.), IEEE Biomedical Engineering Soc. Special Issues of International Journals have been, and will be, published, collecting selected papers from the conference

GROWING OLD AS A ROCK STAR: A FOUR-PART STUDY OF THE AGING VOICE

This dissertation focuses on the aging voice - specifically the aging elite vocal athlete. It is comprised of four components; a series of research studies and a viewpoint piece designed to explore the awareness, struggles, and vocal compensations of aging singers dealing with age related vocal and performance problems. The overarching goal of these studies is to inform the development of a voice care protocol for the aging rock star to guide customized intervention for these elite vocal athletes that is focused on optimizing both vocal output and performance. First, the dissertation introduces and identifies characteristics of the exceptional voice. This involves a new vocal continuum that includes the normal voice, the trained voice, and the exceptional voice. The second component is a qualitative study of older contemporary commercial music (CCM) singers adjustments and accommodations associated with their aging. From this, four overarching themes are identified: modest self-perception of their vocal prowess and its relationship to performance, acute sensitivity to changes in vocal quality, recognition of the critical association of voice quality with their identity as a performer, and an array of accommodations to aging-related vocal changes. The third component of the dissertation is a randomized control trial examining the efficacy of Vocal Function Exercises as a treatment modality for presbyphonia. Analysis revealed that the experimental group improved in select outcome measures including decreased glottic gap, increased upper range, and maximum phonation time at the 6-week post-treatment re-evaluation with no such changes in the control group. The final study investigated the vocal and performing trajectories of six CCM male singers through analysis of video performances across their career. Singers were shown to make accommodations consistent with the reported findings from component two. Such accommodations include decreased total time singing for some singers, accommodations for range changes, and changes to performance. From this study, the Exceptional Voice Protocol was created to provide a customized vocal and performance blueprint for each artist that meets their unique needs for their exceptional voices. Overall, this research indicates that aging CCM singers appear to be experiencing age and performance related vocal changes and are making detectable accommodations to their performance. Additional findings show that Vocal Function Exercises appear to be an efficacious treatment modality for aging voice. Findings from these studies confirm the need for continued research on age-related vocal and performance changes for these performers and guidelines for appropriate habilitation and rehabilitation so these rock stars can continue performing for as long as they desire

Learning-Based Reference-Free Speech Quality Assessment for Normal Hearing and Hearing Impaired Applications

Accurate speech quality measures are highly attractive and beneficial in the design, fine-tuning, and benchmarking of speech processing algorithms, devices, and communication systems. Switching from narrowband telecommunication to wideband telephony is a change within the telecommunication industry which provides users with better speech quality experience but introduces a number of challenges in speech processing. Noise is the most common distortion on audio signals and as a result there have been a lot of studies on developing high performance noise reduction algorithms. Assistive hearing devices are designed to decrease communication difficulties for people with loss of hearing. As the algorithms within these devices become more advanced, it becomes increasingly crucial to develop accurate and robust quality metrics to assess their performance. Objective speech quality measurements are more attractive compared to subjective assessments as they are cost-effective and subjective variability is eliminated. Although there has been extensive research on objective speech quality evaluation for narrowband speech, those methods are unsuitable for wideband telephony. In the case of hearing-impaired applications, objective quality assessment is challenging as it has to be capable of distinguishing between desired modifications which make signals audible and undesired artifacts. In this thesis a model is proposed that allows extracting two sets of features from the distorted signal only. This approach which is called reference-free (nonintrusive) assessment is attractive as it does not need access to the reference signal. Although this benefit makes nonintrusive assessments suitable for real-time applications, more features need to be extracted and smartly combined to provide comparable accuracy as intrusive metrics. Two feature vectors are proposed to extract information from distorted signals and their performance is examined in three studies. In the first study, both feature vectors are trained on various portions of a noise reduction database for normal hearing applications. In the second study, the same investigation is performed on two sets of databases acquired through several hearing aids. Third study examined the generalizability of the proposed metrics on benchmarking four wireless remote microphones in a variety of environmental conditions. Machine learning techniques are deployed for training the models in the three studies. The studies show that one of the feature sets is robust when trained on different portions of the data from different databases and it also provides good quality prediction accuracy for both normal hearing and hearing-impaired applications

Assessing the quality of audio and video components in desktop multimedia conferencing

This thesis seeks to address the HCI (Human-Computer Interaction) research problem of how to establish the level of audio and video quality that end users require to successfully perform tasks via networked desktop videoconferencing. There are currently no established HCI methods of assessing the perceived quality of audio and video delivered in desktop videoconferencing. The transport of real-time speech and video information across new digital networks causes novel and different degradations, problems and issues to those common in the traditional telecommunications areas (telephone and television). Traditional assessment methods involve the use of very short test samples, are traditionally conducted outside a task-based environment, and focus on whether a degradation is noticed or not. But these methods cannot help establish what audio-visual quality is required by users to perform tasks successfully with the minimum of user cost, in interactive conferencing environments. This thesis addresses this research gap by investigating and developing a battery of assessment methods for networked videoconferencing, suitable for use in both field trials and laboratory-based studies. The development and use of these new methods helps identify the most critical variables (and levels of these variables) that affect perceived quality, and means by which network designers and HCI practitioners can address these problems are suggested. The output of the thesis therefore contributes both methodological (i.e. new rating scales and data-gathering methods) and substantive (i.e. explicit knowledge about quality requirements for certain tasks) knowledge to the HCI and networking research communities on the subjective quality requirements of real-time interaction in networked videoconferencing environments. Exploratory research is carried out through an interleaved series of field trials and controlled studies, advancing substantive and methodological knowledge in an incremental fashion. Initial studies use the ITU-recommended assessment methods, but these are found to be unsuitable for assessing networked speech and video quality for a number of reasons. Therefore later studies investigate and establish a novel polar rating scale, which can be used both as a static rating scale and as a dynamic continuous slider. These and further developments of the methods in future lab- based and real conferencing environments will enable subjective quality requirements and guidelines for different videoconferencing tasks to be established

NUTRIENT AND MEDICATION INTAKE OF CHILDREN WITH NEURODEVELOPMENTAL DISORDERS

The incidence of autism continues to rise with no cure or understanding of the cause of the disorder. Approximately one in 150 children will be diagnosed with an (ASD) Autism Spectrum Disorder although recent prevalence data suggest one in 91. The objective of the study is to assess medicinal intake regarding prescription and nonprescription medications of children with Autism Spectrum Disorders and its affect on their nutritional status compared to age, and sex matched healthy children. The study included families of children with autism in which they completed questionnaires and 24‐hour recalls. There were 26 children used within the questionnaire and 13 were utilized in the 24‐hour recall, ranging in age from 2‐11. Results demonstrated that children with autism were not deficient in relation to vital nutrients needed for neurological function. Prescription and nonprescription medications also did not pose many side effects; however, there was slight weight gain in their utilization. Information from the assessments of the child’s nutritional needs and drug nutrient interaction will allow parents, paraprofessionals and healthcare professionals to provide education to families

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy. This edition celebrates twenty years of uninterrupted and succesfully research in the field of voice analysis

Use of automated coding methods to assess motivational behaviour in education

Teachers’ motivational behaviour is related to important student outcomes. Assessing teachers’ motivational behaviour has been helpful to improve teaching quality and enhance student outcomes. However, researchers in educational psychology have relied on self-report or observer ratings. These methods face limitations on accurately and reliably assessing teachers’ motivational behaviour; thus restricting the pace and scale of conducting research. One potential method to overcome these restrictions is automated coding methods. These methods are capable of analysing behaviour at a large scale with less time and at low costs. In this thesis, I conducted three studies to examine the applications of an automated coding method to assess teacher motivational behaviours. First, I systematically reviewed the applications of automated coding methods used to analyse helping professionals’ interpersonal interactions using their verbal behaviour. The findings showed that automated coding methods were used in psychotherapy to predict the codes of a well-developed behavioural coding measure, in medical settings to predict conversation patterns or topics, and in education to predict simple concepts, such as the number of open/closed questions or class activity type (e.g., group work or teacher lecturing). In certain circumstances, these models achieved near human level performance. However, few studies adhered to best-practice machine learning guidelines. Second, I developed a dictionary of teachers’ motivational phrases and used it to automatically assess teachers’ motivating and de-motivating behaviours. Results showed that the dictionary ratings of teacher need support achieved a strong correlation with observer ratings of need support (rfull dictionary = .73). Third, I developed a classification of teachers’ motivational behaviour that would enable more advanced automated coding of teacher behaviours at each utterance level. In this study, I created a classification that includes 57 teacher motivating and de-motivating behaviours that are consistent with self-determination theory. Automatically assessing teachers’ motivational behaviour with automatic coding methods can provide accurate, fast pace, and large scale analysis of teacher motivational behaviour. This could allow for immediate feedback and also development of theoretical frameworks. The findings in this thesis can lead to the improvement of student motivation and other consequent student outcomes