9 research outputs found

    Extraction and Classification of Acoustic Features from Italian Speaking Children with Autism Spectrum Disorders

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    Autism Spectrum Disorders (ASD) are a group of complex developmental conditions whose effects and severity show high intraindividual variability. However, one of the main symptoms shared along the spectrum is social interaction impairments that can be explored through acoustic analysis of speech production. In this paper, we compare 14 Italian-speaking children with ASD and 14 typically developing peers. Accordingly, we extracted and selected the acoustic features related to prosody, quality of voice, loudness, and spectral distribution using the parameter set eGeMAPS provided by the openSMILE feature extraction toolkit. We implemented four supervised machine learning methods to evaluate the extraction performances. Our findings show that Decision Trees (DTs) and Support Vector Machines (SVMs) are the best-performing methods. The overall DT models reach a 100% recall on all the trials, meaning they correctly recognise autistic features. However, half of its models overfit, while SVMs are more consistent. One of the results of the work is the creation of a speech pipeline to extract Italian speech biomarkers typical of ASD by comparing our results with studies based on other languages. A better understanding of this topic can support clinicians in diagnosing the disorder

    Validation of a Brief Prosody Rating Scale for Children with Autism Spectrum Disorder

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    Differences in the speech prosody, or melody of speech, of persons with autism spectrum disorder (ASD) have long been noted by researchers. Yet, despite many studies, researchers have not identified a universal description of speech prosody in ASD. It may be flat or monotonous, not different from typical, or overly variable. However, atypical speech prosody can immediately set someone apart from their peers. This distinction could negatively social, academic, and vocational interactions. For those persons with ASD whose speech prosody is different from typical and interferes with daily functioning, valid, reliable, and efficient assessments of speech prosody are needed. Currently, there are only three validated assessments for speech prosody specific to ASD and none of them are simultaneously valid, reliable, and efficient. The purpose of this study was to design, validate, and establish sufficient reliability of a one-item, 7-point continuous rating scale for screening the speech prosody of children with ASD. Additionally, I investigated whether a brief, online training would improve reliability. The rating scale ranged from 1 (monotonous) to 7 (overly variable). Thirty-five 30-second audio clips from previous studies were chosen from children with ASD and neurotypical development. Three expert speech-language pathologists (SLPs) selected clips for the end and mid points of the scale and developed gold standard ratings. A total of 42 ASHA-certified SLPs with experience in treating children with ASD rated 20 of the audio clips at two time points. Twenty of the SLPs participated the online training prior to rating. Analyses were conducted using linear mixed-effects modeling, which were built using a research-question, theory-based modeling approach. Results indicated moderate levels of reliability, except for intra-rater reliability in the trained group, which was good (ICC = 0.76). The results also partially supported the validity of the scale; however, this prosody rating scale requires further study and development before wide use

    Automated extraction of speech and turn-taking parameters in autism allows for diagnostic classification using a multivariable prediction model

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    Autism spectrum disorder (ASD) is diagnosed on the basis of speech and communication differences, amongst other symptoms. Since conversations are essential for building connections with others, it is important to understand the exact nature of differences between autistic and non-autistic verbal behaviour and evaluate the potential of these differences for diagnostics. In this study, we recorded dyadic conversations and used automated extraction of speech and interactional turn-taking features of 54 non-autistic and 26 autistic participants. The extracted speech and turn-taking parameters showed high potential as a diagnostic marker. A linear support vector machine was able to predict the dyad type with 76.2% balanced accuracy (sensitivity: 73.8%, specificity: 78.6%), suggesting that digitally assisted diagnostics could significantly enhance the current clinical diagnostic process due to their objectivity and scalability. In group comparisons on the individual and dyadic level, we found that autistic interaction partners talked slower and in a more monotonous manner than non-autistic interaction partners and that mixed dyads consisting of an autistic and a non-autistic participant had increased periods of silence, and the intensity, i.e. loudness, of their speech was more synchronous

    A computational study of expressive facial dynamics in children with autism

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    Several studies have established that facial expressions of children with autism are often perceived as atypical, awkward or less engaging by typical adult observers. Despite this clear deficit in the quality of facial expression production, very little is understood about its underlying mechanisms and characteristics. This paper takes a computational approach to studying details of facial expressions of children with high functioning autism (HFA). The objective is to uncover those characteristics of facial expressions, notably distinct from those in typically developing children, and which are otherwise difficult to detect by visual inspection. We use motion capture data obtained from subjects with HFA and typically developing subjects while they produced various facial expressions. This data is analyzed to investigate how the overall and local facial dynamics of children with HFA differ from their typically developing peers. Our major observations include reduced complexity in the dynamic facial behavior of the HFA group arising primarily from the eye region

    Pilot study for subgroup classification for autism spectrum disorder based on dysmorphology and physical measurements in Chinese children

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    Poster Sessions: 157 - Comorbid Medical Conditions: abstract 157.058 58BACKGROUND: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder affecting individuals along a continuum of severity in communication, social interaction and behaviour. The impact of ASD significantly varies amongst individuals, and the cause of ASD can originate broadly between genetic and environmental factors. Objectives: Previous ASD researches indicate that early identification combined with a targeted treatment plan involving behavioural interventions and multidisciplinary therapies can provide substantial improvement for ASD patients. Currently there is no cure for ASD, and the clinical variability and uncertainty of the disorder still remains. Hence, the search to unravel heterogeneity within ASD by subgroup classification may provide clinicians with a better understanding of ASD and to work towards a more definitive course of action. METHODS: In this study, a norm of physical measurements including height, weight, head circumference, ear length, outer and inner canthi, interpupillary distance, philtrum, hand and foot length was collected from 658 Typical Developing (TD) Chinese children aged 1 to 7 years (mean age of 4.19 years). The norm collected was compared against 80 ASD Chinese children aged 1 to 12 years (mean age of 4.36 years). We then further attempted to find subgroups within ASD based on identifying physical abnormalities; individuals were classified as (non) dysmorphic with the Autism Dysmorphology Measure (ADM) from physical examinations of 12 body regions. RESULTS: Our results show that there were significant differences between ASD and TD children for measurements in: head circumference (p=0.009), outer (p=0.021) and inner (p=0.021) canthus, philtrum length (p=0.003), right (p=0.023) and left (p=0.20) foot length. Within the 80 ASD patients, 37(46%) were classified as dysmorphic (p=0.00). CONCLUSIONS: This study attempts to identify subgroups within ASD based on physical measurements and dysmorphology examinations. The information from this study seeks to benefit ASD community by identifying possible subtypes of ASD in Chinese population; in seek for a more definitive diagnosis, referral and treatment plan.published_or_final_versio

    A Holmes and Doyle Bibliography, Volume 5: Periodical Articles--Secondary References, Alphabetical Listing

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    This bibliography is a work in progress. It attempts to update Ronald B. De Waal’s comprehensive bibliography, The Universal Sherlock Holmes, but does not claim to be exhaustive in content. New works are continually discovered and added to this bibliography. Readers and researchers are invited to suggest additional content. Volume 5 includes "passing" or "secondary" references, i.e. those entries that are passing in nature or contain very brief information or content

    A Holmes and Doyle Bibliography, Volume 6: Periodical Articles, Subject Listing, By De Waal Category

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    This bibliography is a work in progress. It attempts to update Ronald B. De Waal’s comprehensive bibliography, The Universal Sherlock Holmes, but does not claim to be exhaustive in content. New works are continually discovered and added to this bibliography. Readers and researchers are invited to suggest additional content. Volume 6 presents the periodical literature arranged by subject categories (as originally devised for the De Waal bibliography and slightly modified here)

    A Holmes and Doyle Bibliography, Volume 9: All Formats—Combined Alphabetical Listing

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    This bibliography is a work in progress. It attempts to update Ronald B. De Waal’s comprehensive bibliography, The Universal Sherlock Holmes, but does not claim to be exhaustive in content. New works are continually discovered and added to this bibliography. Readers and researchers are invited to suggest additional content. This volume contains all listings in all formats, arranged alphabetically by author or main entry. In other words, it combines the listings from Volume 1 (Monograph and Serial Titles), Volume 3 (Periodical Articles), and Volume 7 (Audio/Visual Materials) into a comprehensive bibliography. (There may be additional materials included in this list, e.g. duplicate items and items not yet fully edited.) As in the other volumes, coverage of this material begins around 1994, the final year covered by De Waal's bibliography, but may not yet be totally up-to-date (given the ongoing nature of this bibliography). It is hoped that other titles will be added at a later date. At present, this bibliography includes 12,594 items
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