Computerized Based Analysis for Detection and Severity Assessment of Stuttering

Stuttering Clinical Trial

Official title:

Computerized Based Analysis for Detection and Severity Assessment of Stuttering

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05437627
• Other study ID #: Stuttering using Computer
• Status: Not yet recruiting
• Start date: September 1, 2022
• Est. completion date: October 1, 2024

Study information

• Verified date: June 2022
• Source: Assiut University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

In the light of previous attempts to design and develop automated and objective measures for automatic speech recognition system that detects disfluent speech and assess its severity, yet fully automated measurement of stuttered speech is not available. This study was triggered by the need to design and develop a simple and reliable computerized tool for identification of stuttering and measurement for its severity. Therefore, the aim of this study is to develop a user interface that can work on windows system for the adopted stuttering recognition model which can be used in clinical practice by physicians and therapists.

Description:

Stuttering is a speech disorder in which the normal flow of speech is disrupted by occurrences of dysfluencies, such as repetition, prolongations and blocks (1). Features that have been found to differ between stutterers and nonstutterers are rate of speech and frequency of dysfluent utterances (2).

An Arabic version of stuttering severity instrument (A-SSI) is used to assess the stuttering severity In it, the overall severity score of stuttering is measured by combining the scores of percentages of Stuttered Syllables (%SS), Mean Duration of the Three Longest Stuttering Events (MDTLSE), and Physical Concomitants (PC) (3).

The subjective assessment methods of stuttering are; time-consuming, prone to error, subjective (4), so it is better to automate the measurement of disfluencies using speech recognition technologies and computational intelligence (5).

Speech recognition executes a task similar to what the human brain undertakes (6). Stuttering detection system has three main steps which are acoustic processing, feature extraction and classification/recognition (7). the speech signals are pre-processed (8), and certain features are extracted from them by signal processing techniques, e.g. Mell frequency cepstral coefficients (MFCC) (9). (MFCC) is considered the most popular used feature extraction technique (10).

The classification process contains two steps; training and testing (11). In training process, data is labeled based on the classes and a model is learned. In testing phase: the model is tested and computed the accuracy, sensitivity, and specificity of the classification models (11). Finally, stuttering from non-stuttering speech will be recognized and separated (5) also to assess the severity of stuttered speech.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 120
• Est. completion date: October 1, 2024
• Est. primary completion date: September 30, 2024
• Gender: All
• Age group: 10 Years to 30 Years

Eligibility

Inclusion Criteria:

1. Age: from 10 to 30 years old.

2. Gender: both sexes will be included in the study.

3. The participants in the study group suffering from developmental stuttering (stuttering symptoms was of early childhood onset, intermittent course and dated since early childhood) seeking speech therapy

4. Have language aptitudes coping with his or her chronological age.

Exclusion Criteria:

• 1. Presence of any other speech or language disorders. 2. Mental Retardation. 3. Poor scholastic performances. 4. Presence of any psychiatric or neurologic disorders.

Related Conditions & MeSH terms

• Stuttering

Intervention

Diagnostic Test:
• The Arabic version of Stuttering Severity Instrument-3 (ASSI3) for children and adults
Assessment of stuttering severity: The Arabic version of Stuttering Severity Instrument-3 (ASSI3) for children and adults will be applied for assessment of severity of stuttering. (3). Automatic detection and severity assessment of stuttering using MATLAB version 8.1.0.604 R2013a (7). Stuttering detection system has three main steps which are acoustic processing, feature extraction and classification/recognition

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Assiut University

References & Publications (8)

Andrews G, Craig A, Feyer AM, Hoddinott S, Howie P, Neilson M. Stuttering: a review of research findings and theories circa 1982. J Speech Hear Disord. 1983 Aug;48(3):226-46. Review. — View Citation

Bakker K, Brutten GJ. Speech-related reaction times of stutterers and nonstutterers: diagnostic implications. J Speech Hear Disord. 1990 May;55(2):295-9. — View Citation

Enderby PM, John A. Therapy outcome measures in speech and language therapy: comparing performance between different providers. Int J Lang Commun Disord. 1999 Oct-Dec;34(4):417-29. — View Citation

O'Brian S, Packman A, Onslow M, O'Brian N. Measurement of stuttering in adults: comparison of stuttering-rate and severity-scaling methods. J Speech Lang Hear Res. 2004 Oct;47(5):1081-7. — View Citation

Prasse JE, Kikano GE. Stuttering: an overview. Am Fam Physician. 2008 May 1;77(9):1271-6. Review. — View Citation

Prins D, Ingham RJ. Evidence-based treatment and stuttering--historical perspective. J Speech Lang Hear Res. 2009 Feb;52(1):254-63. doi: 10.1044/1092-4388(2008/07-0111). Epub 2008 Aug 11. Review. Erratum in: J Speech Lang Hear Res. 2009 Apr;52(2):570. — View Citation

SHERMAN D. Clinical and experimental use of the Iowa Scale of Severity of Stuttering. J Speech Hear Disord. 1952 Sep;17(3):316-20. — View Citation

Yairi E. Subtyping stuttering I: a review. J Fluency Disord. 2007;32(3):165-96. Epub 2007 Apr 24. Review. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Assessment of stuttering severity:	using both subjective method as The Arabic version of Stuttering Severity Instrument-3 (ASSI3) for children and adults and objective method asAutomatic detection and severity assessment of stuttering	baseline