‘Listening’ To Dyslexic Children’s Reading: The Transcription And Segmentation Accuracy For ASR

Authors

  • Husniza Husni Human-Centered Computing Research Lab, School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Nik Nurhidayat Nik Him Human-Centered Computing Research Lab, School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Mohamed M. Radi Emirates Canadian University College, Umm Al Quwain, United Arab Emirates
  • Yuhanis Yusof Human-Centered Computing Research Lab, School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Siti Sakira Kamaruddin Human-Centered Computing Research Lab, School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia

Keywords:

Automatic Transcription and Phonetic Labelling, Automatic Speech Recognition, Dyslexic Children Reading,

Abstract

Dyslexic children read with a lot of highly phonetically similar error that is a challenge for speech recognition (ASR). Listening to the highly phonetically similar errors are indeed difficult even for a human. To enable a computer to ‘listen’ to dyslexic children’s reading is even more challenging as we have to ‘teach’ the computers to recognize the readings as well as to adapt to the highly phonetically similar errors they make when reading. This is even more difficult when segmenting and labelling the read speech for processing prior to training an ASR. Hence, this paper presents and discusses the effects of highly phonetically similar errors on automatic transcription and segmentation accuracy and how it is somehow influenced by the spoken pronunciations. A number of 585 files of dyslexic children’s reading is used for manual transcription, force alignment, and training. The recognition of ASR engine using automatic transcription and phonetic labelling obtained an optimum result, which is with 23.9% WER and 18.1% FAR. The results are almost similar with ASR engine using manual transcription 23.7% WER and 17.9% FAR.

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Published

2017-09-15

How to Cite

Husni, H., Nik Him, N. N., M. Radi, M., Yusof, Y., & Kamaruddin, S. S. (2017). ‘Listening’ To Dyslexic Children’s Reading: The Transcription And Segmentation Accuracy For ASR. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-11), 45–49. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2736

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