A two-case study of coarticulation in stuttered speech. An articulatory approach

Didirková, Ivana; Hirsch, Fabrice

doi:10.1080/02699206.2019.1660913

Cited by 8 publications

(3 citation statements)

References 23 publications

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“…He theorizes that disfluencies occur during a fault line, which corresponds to the interval when muscular activity due to a sound which have been produced is going off and muscular movements for the following sound is going on. However in a recent study, Didirková and Hirsch [47] show, thanks to EMA data, that stuttering is not a coarticulation trouble. They found correct coarticulatory patterns in the fluent and stuttered utterances.…”

Section: Characteristics Of Stuttered Speechmentioning

confidence: 92%

Machine Learning for Stuttering Identification: Review, Challenges and Future Directions

Sheikh¹,

Sahidullah²,

Hirsch³

et al. 2021

Preprint

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Stuttering is a speech disorder during which the flow of speech is interrupted by involuntary pauses and repetition of sounds. Stuttering identification is an interesting interdisciplinary domain research problem which involves pathology, psychology, acoustics, and signal processing that makes it hard and complicated to detect. Recent developments in machine and deep learning have dramatically revolutionized speech domain, however minimal attention has been given to stuttering identification. This work fills the gap by trying to bring researchers together from interdisciplinary fields. In this paper, we review comprehensively acoustic features, statistical and deep learning based stuttering/disfluency classification methods. We also present several challenges and possible future directions.

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Section: Characteristics Of Stuttered Speechmentioning

confidence: 92%

Machine Learning for Stuttering Identification: Review, Challenges and Future Directions

Sheikh¹,

Sahidullah²,

Hirsch³

et al. 2021

Preprint

Self Cite

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“…Thus, one of the most important problems for annotating speech in people who stutter is to define precise criteria for differentiating between a lengthening due to stuttering, which is in general supposed to be due to a motor-related problem, e.g. in a transition between the disfluent and the subsequent sound (e.g., Didirková & Hirsch, 2020), and a lengthening due to other linguistic processes, such as formulation (Lickley, 2017).…”

Section: Models For Atypical Speech Productionmentioning

confidence: 99%

Towards an inclusive system for the annotation of (dis)fluency in typical and atypical speech

Crible

Didirková

Dodane

et al. 2022

Clinical Linguistics & Phonetics

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Towards an inclusive system for the annotation of (dis)fluency in typical and atypical speechThis paper presents an operational annotation system for (dis)fluencies in typical and atypical speech, based on existing standard annotation schemes previously established in the literature. Grounded in a functional approach to (dis)fluency, we address some of the conceptual and technical limitations found in previous annotation models, and offer an integrated and inclusive system which is compatible with different multi-layered annotation software such as Praat or ELAN. Our aim is twofold: to create comparable annotated corpora both in typical and atypical speech, and to provide natural language processing and the health sector with applications for diagnostic and therapy in speech disorders.

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“…More recently Didirková and Hirsch (2019) studied coarticulation of articulatory movements for both fluent and disfluent syllables produced by two PWS. They performed a kinematic analysis of the speech gestures involved in the transitions between a stuttered phone and its preceding and subsequent phones by means of electromagnetic articulography ( Schönle et al, 1987 ; Hasegawa-Johnson, 1998 ).…”

Section: Introductionmentioning

confidence: 99%

Coarticulatory Aspects of the Fluent Speech of French and Italian People Who Stutter Under Altered Auditory Feedback

2020

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A two-case study of coarticulation in stuttered speech. An articulatory approach

Cited by 8 publications

References 23 publications

Machine Learning for Stuttering Identification: Review, Challenges and Future Directions

Machine Learning for Stuttering Identification: Review, Challenges and Future Directions

Towards an inclusive system for the annotation of (dis)fluency in typical and atypical speech

Coarticulatory Aspects of the Fluent Speech of French and Italian People Who Stutter Under Altered Auditory Feedback

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