Tabby Talks: An automated tool for the assessment of childhood apraxia of speech

Shahin, Mostafa; Ahmed, Beena; Parnandi, Avinash; Karappa, Virendra; McKechnie, Jacqueline; Ballard, Kirrie J.; Gutierrez‐Osuna, Ricardo

doi:10.1016/j.specom.2015.04.002

Cited by 35 publications

(21 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Effective procedures are needed to obtain linguistically adequate continuous speech samples from children with low verbal skills who may produce some phrase-length speech with supportive assessment. Repeated continuous speech sampling in environmentally valid contexts using mobile recording instrumentation is becoming an option, with the goal of providing automated data acquisition and reduction for the types of speech analyses described in the present article (e.g., Dykstra et al, 2013;Shahin et al, 2015). It is also possible that the pause and speech elements of the PM are occurring in other simpler speech tasks in the present assessment protocol or could be evoked using other speech tasks that do not require continuous speech (Kearney et al, 2015).…”

Section: Pm Research Needsmentioning

confidence: 99%

A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: IV. The Pause Marker Index

Shriberg

Strand

Fourakis

et al. 2017

J Speech Lang Hear Res

View full text Add to dashboard Cite

Purpose: Three previous articles provided rationale, methods, and several forms of validity support for a diagnostic marker of childhood apraxia of speech (CAS), termed the pause marker (PM). Goals of the present article were to assess the validity and stability of the PM Index (PMI) to scale CAS severity. Method: PM scores and speech, prosody, and voice precision-stability data were obtained for participants with CAS in idiopathic, neurogenetic, and complex neurodevelopmental disorders; adult-onset apraxia of speech consequent to stroke and primary progressive apraxia; and idiopathic speech delay. Three studies were completed including criterion and concurrent validity studies of the PMI and a temporal stability study of the PMI using retrospective case studies. Results: PM scores were significantly correlated with other signs of CAS precision and stability. The best fit of the distribution of PM scores to index CAS severity was obtained by dividing scores into 4 ordinal severity classifications: mild, mild-moderate, moderate-severe, and severe. Severity findings for the 4 classifications and retrospective longitudinal findings from 8 participants with CAS supported the validity and stability of the PMI. Conclusion: Findings support research and clinical use of the PMI to scale the severity of CAS.A four-article series (Shriberg et al., 2017a(Shriberg et al., , 2017b(Shriberg et al., , 2017c, and the present article) to develop and assess the theoretical and clinical utility of a singlesign, behavioral marker of childhood apraxia of speech (CAS) poses the following three questions: 1.Do findings from construct and criterion validity studies support the diagnostic accuracy of a behavioral marker, the pause marker (PM), to discriminate CAS from speech delay (SD)?2. Do findings from the PM and other measures support the hypothesis of core representational and transcoding deficits in CAS, and is the PM theoretically coherent with those deficits?3. Do findings from cross-sectional and retrospective longitudinal case studies support an ordinal scale of PM scores, the Pause Marker Index (PMI), to quantify the severity of CAS for research and clinical applications?The short-term goal of the PM is to provide a behavioral marker of CAS for research and clinical practice. A longer term goal of the PM is to provide quantitative inclusionary and exclusionary criteria to identify participants who are true positive for CAS in studies to identify and validate a biomarker of CAS. The present article addresses both goals. As proposed in the first article in this series (PM I; Shriberg et al., 2017a, Table 1), a highly valued attribute of diagnostic markers is generality, that is, a marker has research and clinical utility beyond identifying presence or absence of a disorder. In the present context, a behavioral marker of CAS has research and clinical generality when in addition to being diagnostically sensitive to and specific for a prior, active, and/or future disorder, it also quantifies the severity of the disorder. The three...

show abstract

Section: Pm Research Needsmentioning

confidence: 99%

A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: IV. The Pause Marker Index

Shriberg

Strand

Fourakis

et al. 2017

J Speech Lang Hear Res

View full text Add to dashboard Cite

show abstract

“…There are tools that are focused on training basic phonation skills in children with neuromuscular disorders, training the articulatory level of language or introducing the impaired child population to language understanding [16,17]. Other tools incorporate speech technologies to assist automated speech therapy in childhood apraxia of speech (CAS) [18], whereas others give a visual feedback of the positioning of the articulatory elements to produce different sounds [19]. Diagnosing and training tools for stuttering problems in children have also been developed [20].…”

Section: Introductionmentioning

confidence: 99%

Automatic Assessment of Prosodic Quality in Down Syndrome: Analysis of the Impact of Speaker Heterogeneity

et al. 2019

View full text Add to dashboard Cite

Prosody is a fundamental speech element responsible for communicative functions such as intonation, accent and phrasing, and prosodic impairments of individuals with intellectual disabilities reduce their communication skills. Yet, technological resources have paid little attention to prosody. This study aims to develop an automatic classifier to predict the prosodic quality of utterances produced by individuals with Down syndrome, and to analyse how inter-individual heterogeneity affects assessment results. A therapist and an expert in prosody judged the prosodic appropriateness of a corpus of Down syndrome' utterances collected through a video game. The judgments of the expert were used to train an automatic classifier that predicts prosodic quality by using a set of fundamental frequency, duration and intensity features. The classifier accuracy was 79.3% and its true positive rate 89.9%. We analyzed how informative each of the features was for the assessment and studied relationships between participants' developmental level and results: interspeaker variability conditioned the relative weight of prosodic features for automatic classification and participants' developmental level was related to the prosodic quality of their productions. Therefore, since speaker variability is an intrinsic feature of individuals with Down syndrome, it should be considered to attain an effective automatic prosodic assessment system.

show abstract

“…Previous work in clinical applications of ASR have focused on particular disorders, such as childhood apraxia of speech (CAS) [8]. The aim of this system is to facilitate remote delivery and the monitoring of therapy by skilled SLPs, achieved through modules which detect voice activity and verify lexical stress and pronunciation.…”

Section: Introductionmentioning

confidence: 99%

Automated Screening of Speech Development Issues in Children by Identifying Phonological Error Patterns

Ward¹,

Stefani²,

Smith³

et al. 2016

Interspeech 2016

View full text Add to dashboard Cite

A proof of concept system is developed to provide a broad assessment of speech development issues in children. It has been designed to enable non-experts to complete an initial screening of children's speech with the aim of reducing the workload on Speech Language Pathology services. The system was composed of an acoustic model trained by neural networks with split temporal context features and a constrained HMM encoded with the knowledge of Speech Language Pathologists. Results demonstrated the system was able to improve PER by 33% compared with standard HMM decoders, with a minimum PER of 19.03% achieved. Identification of Phonological Error Patterns with up to 94% accuracy was achieved despite utilizing only a small corpus of disordered speech from Australian children. These results indicate the proposed system is viable and the direction of further development are outlined in the paper.

show abstract

Tabby Talks: An automated tool for the assessment of childhood apraxia of speech

Cited by 35 publications

References 63 publications

A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: IV. The Pause Marker Index

A Diagnostic Marker to Discriminate Childhood Apraxia of Speech From Speech Delay: IV. The Pause Marker Index

Automatic Assessment of Prosodic Quality in Down Syndrome: Analysis of the Impact of Speaker Heterogeneity

Automated Screening of Speech Development Issues in Children by Identifying Phonological Error Patterns

Contact Info

Product

Resources

About