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Published in: Wireless Personal Communications 2/2022

14-06-2022

A Review on Speech Disorders and Processing of Disordered Speech

Authors: Audre Arlene Anthony, Chandreshekar Mohan Patil, Jagadeesh Basavaiah

Published in: Wireless Personal Communications | Issue 2/2022

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Abstract

Speech disorder refers to the situation that affects the ability of a person to produce sounds that generates words. People of any age can be affected by speech disorders. Speech disorders symptoms varies broadly contingent on the cause and the disorder severity. Multiple speech disorders can be developed in the people with different symptoms. Approximately one-fifth of theworld’s population suffer or have suffered from voice and speech production disorders due to diseases or some other dysfunction. Thus, there is a clear need for objective ways to evaluate the quality of voice and speech as well as its link to vocal fold activity, to evaluate the complex interaction between the larynx and voluntary movements of the articulators (i.e., lips, teeth, tongue, velum, jaw, etc.), or to evaluate disfluencies at the language level. With advances in speech signal processing and natural language processing, there has been recent interest in developing tools to detect more subtle changes in cognitive-linguistic function. This paper discusses on various speech disorders in children and adults such as apraxia, stuttering, voice disorders involving the larynx, Aphasia and dysarthria. This paper also presents a survey on different methods used for processing speech disorders.
Literature
2.
go back to reference Alharbi S., Hasan M., Simons A.J.H., Brumfitt S., Green P. (2017) Detecting Stuttering Events in Transcripts of Children’s Speech. In: Camelin N., Estève Y., Martín-Vide C. (eds) Statistical Language and Speech Processing. SLSP 2017. Lecture Notes in Computer Science, vol 10583. Springer, Cham Alharbi S., Hasan M., Simons A.J.H., Brumfitt S., Green P. (2017) Detecting Stuttering Events in Transcripts of Children’s Speech. In: Camelin N., Estève Y., Martín-Vide C. (eds) Statistical Language and Speech Processing. SLSP 2017. Lecture Notes in Computer Science, vol 10583. Springer, Cham
5.
go back to reference Kothalkar, P. V., Rudolph, J., Dollaghan, C., McGlothlin, J., Campbell, T. F., Hansen, J. H. L., Automatic Screening to Detect ’At Risk’ Child Speech Samples using a Clinical Group Verification framework*. (2018). 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Honolulu, HI, 2018, 4909–4913. Kothalkar, P. V., Rudolph, J., Dollaghan, C., McGlothlin, J., Campbell, T. F., Hansen, J. H. L., Automatic Screening to Detect ’At Risk’ Child Speech Samples using a Clinical Group Verification framework*. (2018). 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Honolulu, HI, 2018, 4909–4913.
6.
go back to reference Hanani, A., Attari, M., Farakhna, A., Joma'A, A., Hussein, M., Taylor, S. (2016) Automatic Identification of Articulation Disorders for Arabic Children Speakers. Proc. Workshop on Child Computer Interaction, 35–39. Hanani, A., Attari, M., Farakhna, A., Joma'A, A., Hussein, M., Taylor, S. (2016) Automatic Identification of Articulation Disorders for Arabic Children Speakers. Proc. Workshop on Child Computer Interaction, 35–39.
7.
go back to reference Vikram, C., Tripathi, A., Kalita, S., Prasanna,SM. (2018) "Estimation of hypernasality scores from cleft lip and palate speech", Proc. Interspeech, 1701–1705 Vikram, C., Tripathi, A., Kalita, S., Prasanna,SM. (2018) "Estimation of hypernasality scores from cleft lip and palate speech", Proc. Interspeech, 1701–1705
9.
go back to reference Wang, X., Du, J., Sun, L., Wang, Q., Lee, C., A Progressive Deep Learning Approach to Child Speech Separation. (2018). 11th International Symposium on Chinese Spoken Language Processing (ISCSLP). Taipei City, Taiwan, 2018, 76–80. Wang, X., Du, J., Sun, L., Wang, Q., Lee, C., A Progressive Deep Learning Approach to Child Speech Separation. (2018). 11th International Symposium on Chinese Spoken Language Processing (ISCSLP). Taipei City, Taiwan, 2018, 76–80.
10.
go back to reference Shahin, M., Gutierrez-Osuna, R., Ahmed, B. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, 2016 6480–6484. Shahin, M., Gutierrez-Osuna, R., Ahmed, B. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, 2016 6480–6484.
11.
go back to reference Teshaboyeva, G. (2020). Speech defects in young children and ways to overcome them. ACADEMICIA International Multidisciplinary Research Journal, 10(6), 1761–1767. CrossRef Teshaboyeva, G. (2020). Speech defects in young children and ways to overcome them. ACADEMICIA International Multidisciplinary Research Journal, 10(6), 1761–1767. CrossRef
12.
go back to reference Ruksenaite, J., Volkmer, A., Jiang, J., Johnson, J. C., Marshall, C. R., Warren, J. D., & Hardy, C. J. (2021). Primary progressive Aphasia: Toward a pathophysiological synthesis. Current Neurology and Neuroscience Reports, 21(3), 1–2. CrossRef Ruksenaite, J., Volkmer, A., Jiang, J., Johnson, J. C., Marshall, C. R., Warren, J. D., & Hardy, C. J. (2021). Primary progressive Aphasia: Toward a pathophysiological synthesis. Current Neurology and Neuroscience Reports, 21(3), 1–2. CrossRef
13.
go back to reference Zhang, Z., Xu, Q., Joshi, R.M. (2020) A meta‐analysis on the effectiveness of intervention in children with primary speech and language delays/disorders: focusing on China and the United States. Clin. Psychol. Psychother Zhang, Z., Xu, Q., Joshi, R.M. (2020) A meta‐analysis on the effectiveness of intervention in children with primary speech and language delays/disorders: focusing on China and the United States. Clin. Psychol. Psychother
14.
go back to reference Horton, R (2020) Systems-based approaches to speech-language pathology service delivery for school age children. In: Cases on Communication Disorders in Culturally Diverse Populations, pp. 113–136. IGI Global Horton, R (2020) Systems-based approaches to speech-language pathology service delivery for school age children. In: Cases on Communication Disorders in Culturally Diverse Populations, pp. 113–136. IGI Global
15.
go back to reference Rumbach, A. F., Clayton, N. A., Muller, M. J., & Maitz, P. K. (2016). The speech-language pathologist’s role in multidisciplinary burn care: An international perspective. Burns, 42(4), 863–871. CrossRef Rumbach, A. F., Clayton, N. A., Muller, M. J., & Maitz, P. K. (2016). The speech-language pathologist’s role in multidisciplinary burn care: An international perspective. Burns, 42(4), 863–871. CrossRef
16.
go back to reference Jothi, K., Sivaraju, S., Yawalkar, P (2021) AI-based speech-language therapy using speech quality parameters for aphasia person: a comprehensive review. In: 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 5382 -5392 Jothi, K., Sivaraju, S., Yawalkar, P (2021) AI-based speech-language therapy using speech quality parameters for aphasia person: a comprehensive review. In: 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 5382 -5392
17.
go back to reference Kohlschein, C., Schmitt, M., Schuller, B., Jeschke, S., Werner, C (2017) A machine learning-based system for the automatic evaluation of aphasia speech. In: IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom) Kohlschein, C., Schmitt, M., Schuller, B., Jeschke, S., Werner, C (2017) A machine learning-based system for the automatic evaluation of aphasia speech. In: IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom)
18.
go back to reference Gasparetti, F., De Medio, C., Limongelli, C., Sciarrone, F., & Temperini, M. (2018). Prerequisites between learning objects: Automatic extraction based on a machine learning approach. Telematics and Informatics, 35(3), 595–610. CrossRef Gasparetti, F., De Medio, C., Limongelli, C., Sciarrone, F., & Temperini, M. (2018). Prerequisites between learning objects: Automatic extraction based on a machine learning approach. Telematics and Informatics, 35(3), 595–610. CrossRef
19.
go back to reference Aishwarya, J., Kundapur, P., Kumar, S., Hareesha, K.S (2018) Kannada speech recognition system for Aphasic people. In: International Conference on Advances in Computing, Communications, and Informatics (ICACCI), 1753–1756 Aishwarya, J., Kundapur, P., Kumar, S., Hareesha, K.S (2018) Kannada speech recognition system for Aphasic people. In: International Conference on Advances in Computing, Communications, and Informatics (ICACCI), 1753–1756
20.
go back to reference Briffa, C., & Porter, J. (2013). A systematic review of the collaborative clinical education model to inform speech-language pathology practice. International Journal of Speech-Language Pathology, 15(6), 564–574. CrossRef Briffa, C., & Porter, J. (2013). A systematic review of the collaborative clinical education model to inform speech-language pathology practice. International Journal of Speech-Language Pathology, 15(6), 564–574. CrossRef
Metadata
Title
A Review on Speech Disorders and Processing of Disordered Speech
Authors
Audre Arlene Anthony
Chandreshekar Mohan Patil
Jagadeesh Basavaiah
Publication date
14-06-2022
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 2/2022
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-022-09812-w

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