Production of syllable stress in speakers with autism spectrum disorders

Paul, Rhea; Bianchi, Nancy; Augustyn, Amy; Klin, Ami; Volkmar, Fred R.

doi:10.1016/j.rasd.2007.04.001

Cited by 63 publications

(77 citation statements)

References 27 publications

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“…We apply these methods in a research protocol that addresses several methodological shortcomings discussed by McCann and Peppé (2003) in their review of prosody in ASD, by using samples of individuals with ASD that (i) are well-characterized; (ii) matched on key variables such as non-verbal IQ and age; (iii) have adequate sizes (most studies reviewed by McCann & Peppé have samples of fewer than 10 individuals, and only three out of thirteen studies reviewed have samples larger than 15); and (iv) have an adequately narrow age range (e.g., the studies with the largest numbers of participants, regrettably, have wide age ranges: 7–32 years in Fine, J., Bartolucci, G., Ginsberg, G., & Szatmari (1991); 10–50 years in Shriberg et al (2001); and, in a more recent study not covered by McCann & Peppé, 7–28 years in Paul, Bianchi, Augustyn, Klin, & Volkmar (2008)). …”

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confidence: 99%

Computational prosodic markers for autism

Santen

Prud’hommeaux

Black

2010

Autism

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We present results obtained with new instrumental methods for the acoustic analysis of prosody to evaluate prosody production by children with Autism Spectrum Disorder (ASD) and Typical Development (TD). Two tasks elicit focal stress, one in a vocal imitation paradigm, the other in a picture-description paradigm; a third task also uses a vocal imitation paradigm, and requires repeating stress patterns of two-syllable nonsense words. The instrumental methods differentiated significantly between the ASD and TD groups in all but the focal stress imitation task. The methods also showed smaller differences in the two vocal imitation tasks than in the picture-description task, as was predicted. In fact, in the nonsense word stress repetition task, the instrumental methods showed better performance for the ASD group. The methods also revealed that the acoustic features that predict auditory-perceptual judgment are not the same as those that differentiate between groups. Specifically, a key difference between the groups appears to be a difference in the balance between the various prosodic cues, such as pitch, amplitude, and duration, and not necessarily a difference in the strength or clarity with which prosodic contrasts are expressed

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confidence: 99%

Computational prosodic markers for autism

Santen

Prud’hommeaux

Black

2010

Autism

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“…However, it is worth pointing out that perception of syllable stress was not associated with communicative ability in ASD, indicating that factors other than perceptive prosody sensitivities may contribute to the development of communication deficits. Previous studies show that children with ASD do not emulate the speech of their peers like typically developing children do (Baron-Cohen & Staunton, 1994;Paul et al, 2008). For example, their stress production ability is not qualitatively comparable to the level of their peers (Diehl & Paul, 2013;Paul et al, 2005a).…”

Section: Discussionmentioning

confidence: 93%

“…For example, their stress production ability is not qualitatively comparable to the level of their peers (Diehl & Paul, 2013;Paul et al, 2005a). This lack of speech emulation is thought to be an important contributing factor to the social communication deficits observed in speakers with ASD (Baron-Cohen & Staunton, 1994;Paul et al, 2008). Receptive prosody precedes and influences the development of expressive prosody.…”

Section: Discussionmentioning

confidence: 99%

“…atypical placement of stress cues within the utterance), pitch variation (i.e. 'robotic or exaggerated intonation), phrasing and rhythm (e.g., Baltaxe, 1984;Baltaxe & Guthrie, 1987;Bonneh, Levanon, Dean-Pardo, Lossos, & Adini, 2011;DePape, Chen, Hall, & Trainor, 2012;Diehl & Paul, 2013; Kujala, Lepistö, & Näätänen, 2013;McCann & Peppé, 2003;Paul et al, 2005aPaul et al, , 2005bPaul, Bianchi, Augustyn, Klin, & Volkmar 2008;Shriberg et al, 2001). These verbal behaviours are present at infancy and highly persistent with relatively little change over time (Kanner, 1971;Simmons & Baltaxe, 1975).…”

Section: Introductionmentioning

confidence: 99%

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Relations Among Detection of Syllable Stress, Speech Abnormalities, and Communicative Ability in Adults With Autism Spectrum Disorders

Kargas

López

Morris

et al. 2016

J Speech Lang Hear Res

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2 AbstractPurpose: To date the literature on perception of affective, pragmatic and grammatical prosody abilities in autism spectrum disorders (ASD) has been sparse and contradictory. Interestingly, the primary perception of syllable stress within the word structure, which is crucial for all prosody functions, remains relatively unexplored in ASD. Thus, the current study explored syllable stress perception sensitivity and its relation to speech production abnormalities and communicative ability in adults with ASD.Method: A same-different syllable stress perception task using pairs of identical foursyllable words was delivered to 42 adults with/without high-functioning ASD, matched for age, to investigate primary speech perception ability in ASD. Speech production and communicative ability in ASD was measured using the Autism Diagnostic Observation Schedule.Results: As predicted, the results showed that adults with ASD were less sensitive in making judgments about syllable stress relative to controls. Also, partial correlations revealed a key association of speech production abnormalities with stress perception sensitivity, rather than communicative ability per se.Conclusions: Our findings provide empirical evidence for deficits on primary syllable stress perception in ASD and its role on socio-communicative difficulties. This information could facilitate the development of effective interventions for speech and language therapy and social communication.

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“…Paul et al [46] investigate stress production by ASD individuals in a nonsense syllable imitation task. The aim was to establish whether ASD speakers produce stressed syllables differently from typically developing (TD) peers.…”

Section: Autism Spectrum Disordersmentioning

confidence: 99%

“You’re as Sick as You Sound”: Using Computational Approaches for Modeling Speaker State to Gauge Illness and Recovery

Hirschberg

Hjalmarsson²,

Elhadad³

2010

Advances in Speech Recognition

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Recently, researchers in computer science and engineering have begun to explore the possibility of finding speech-based correlates of various medical conditions using automatic, computational methods. If such language cues can be identified and quantified automatically, this information can be used to support diagnosis and treatment of medical conditions in clinical settings and to further fundamental research in understanding cognition. This chapter reviews computational approaches that explore communicative patterns of patients who suffer from medical conditions such as depression, autism spectrum disorders, schizophrenia, and cancer. There are two main approaches discussed: research that explores features extracted from the acoustic signal and research that focuses on lexical and semantic features. We also present some applied research that uses computational methods to develop assistive technologies. In the final sections we discuss issues related to and the future of this emerging field of research. Keywords IntroductionMany medical conditions (e.g., depression, autism spectrum disorders (ASD), schizophrenia, as well as cancer) affect the communication patterns of the individuals who suffer from them. Researchers in psychology and psycho-linguistics have a long tradition of studying the speech and language of patients who suffer from these conditions to identify cues, with the hope of leveraging these cues for both

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Production of syllable stress in speakers with autism spectrum disorders

Cited by 63 publications

References 27 publications

Computational prosodic markers for autism

Computational prosodic markers for autism

Relations Among Detection of Syllable Stress, Speech Abnormalities, and Communicative Ability in Adults With Autism Spectrum Disorders

“You’re as Sick as You Sound”: Using Computational Approaches for Modeling Speaker State to Gauge Illness and Recovery

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