Author : Sulaiman S. AlDahri
Affiliation : King Abdulaziz City for Science and
Technology, Riyadh
Country :
Saudi Arabia
Category : Computer Science & Information Technology
Volume, Issue,
Month, Year
: 6, 5, November, 2016
ABSTRACT
Signal processing in current days is under
studying. One of these studies focuses on speech processing. Speech signal have
many important features. One of them is Voice Onset Time (VOT). This feature
only appears in stop sounds. The human auditory system can utilize the VOT to
differentiate between voiced and unvoiced stops like /p/ and /b/ in the English
language. By VOT feature we can classify and detect languages and dialects. The
main reason behind choosing this subject is that the researches in analyzing
Arabic language in this field are not enough and automatic detection of VOT
value in Modern Standard Arabic (MSA) is a new idea. In this paper, we will
focus on designing an algorithm that will be used to detect the VOT value in
MSA language automatically depending on the power signal. We apply this
algorithm only on the voiced stop sounds /b/, /d/ and /d? /, and compare that
VOT values automatically generated by the algorithm with the manual values
calculated by reading the spectrogram. We created the corpus, and used CV-CV-CV
format for each word, the target stop consonant is in the middle of word. The
algorithm resulted in a high accuracy, and the error rate was 0.80%, 26.62% and
11.71% for the three stop voiced sounds /d/, /d? / and /b/ respectively . The
standard deviation was low in /d/ sound because it is easy to pronounce, and
high in /d? / sound because it is unique and difficult to pronounce.
Keyword : Arabic, VOT, MSA, POA, TEO
For More Details : https://airccj.org/CSCP/vol6/csit65205.pdf
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