This paper reviews the state-of-the-art an automatic speech recognition (ASR) based approach for speech therapy of aphasic patients. Aphasia is a condition in which the affected person suffers from speech and language disorder resulting from a stroke or brain injury. Since there is a growing body of evidence indicating the possibility of improving the symptoms at an early stage, ASR based solutions are increasingly being researched for speech and language therapy. ASR is a technology that transfers human speech into transcript text by matching with the system’s library. This is particularly useful in speech rehabilitation therapies as they provide accurate, real-time evaluation for speech input from an individual with speech disorder. ASR based approaches for speech therapy recognize the speech input from the aphasic patient and provide real-time feedback response to their mistakes. However, the accuracy of ASR is dependent on many factors such as, phoneme recognition, speech continuity, speaker and environmental differences as well as our depth of knowledge on human language understanding. Hence, the review examines recent development of ASR technologies and its performance for individuals with speech and language disorders.
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14 September 2017
ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING: FROM THEORY TO APPLICATIONS: Proceedings of the International Conference on Electrical and Electronic Engineering (IC3E 2017)
14–15 August 2017
Johor, Malaysia
Research Article|
September 14 2017
Automatic speech recognition (ASR) based approach for speech therapy of aphasic patients: A review
Norezmi Jamal;
Norezmi Jamal
b)
1
Microelectronic and Nanotechnology Shamsuddin Research Centre (MiNT-SRC), Universiti Tun Hussein Onn Malaysia
, 86400 Parit Raja, Batu Pahat, Johor, Malaysia
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Shahnoor Shanta;
Shahnoor Shanta
a)
2
Department of Electrical Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia
, 86400 Parit Raja, Batu Pahat, Johor, Malaysia
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Farhanahani Mahmud;
Farhanahani Mahmud
c)
1
Microelectronic and Nanotechnology Shamsuddin Research Centre (MiNT-SRC), Universiti Tun Hussein Onn Malaysia
, 86400 Parit Raja, Batu Pahat, Johor, Malaysia
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MNAH Sha’abani
MNAH Sha’abani
d)
3
Department of Electrical Engineering, Centre of Diploma Studies, Universiti Tun Hussein Onn Malaysia
, 86400 Parit Raja, Batu Pahat, Johor, Malaysia
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a)
Corresponding author: [email protected]
AIP Conf. Proc. 1883, 020028 (2017)
Citation
Norezmi Jamal, Shahnoor Shanta, Farhanahani Mahmud, MNAH Sha’abani; Automatic speech recognition (ASR) based approach for speech therapy of aphasic patients: A review. AIP Conf. Proc. 14 September 2017; 1883 (1): 020028. https://doi.org/10.1063/1.5002046
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