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| Segmentation of Malay Syllables in Connected Digit Speech Using Statistical Approach
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Source |
International Journal of Computer Science and Security (IJCSS) |
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Table of Contents |
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Volume: 2 Issue: 1 |
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Pages: 1-86 |
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Publication
Date: February 2008 |
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ISSN
(Online): 1985-1553 |
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Pages |
23 - 33 |
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Author(s) |
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Published
Date |
30-02-2008 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
Colleague |
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KEYWORDS: Speech Segmentation, Divergence Algorithm, Brandt’s Algorithm |
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| This study present segmentation of syllables in Malay connected digit speech.
Segmentation was done in time domain signal using statistical approaches
namely the Brandt’s Generalized Likelihood Ratio (GLR) algorithm and
Divergence algorithm. These approaches basically detect abrupt changes of
energy signal in order to determine the segmentation points. Patterns used in this
experiment are connected digits of 11 speakers spoken in read mode in lab
environment and spontaneous mode in classroom environment. The aim of this
experiment is to get close match between reference points and automatic
segmentation points. Experiments were conducted to see the effect of number of
the auto regressive model order p and sliding window length L in Brandt’s
algorithm and Divergence algorithm in giving better match of the segmentation
points. This paper reports the finding of segmentation experiment using four
criterions ie. the insertion, omissions, accuracy and segmentation match between
the algorithms. The result shows that divergence algorithm performed only
slightly better and has opposite effect of the testing parameter p and L compared
to Brandt’s GLR. Read mode in comparison to spontaneous mode has better
match and less omission but less accuracy and more insertion. |
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A. V. Aquino and Y. J. A. Barria, “Change Detection in Time Series Using the Maximal Overlap Discrete Wavelet Transform”. Lat. Am. appl. res. 39(2), pp. 145-152., 2009.
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H. Farsi, “Improvement of Minimum Tracking in Minimum Statistics Noise Estimation Method”, Signal Processing: An International Journal (SPIJ), 4(1), pp. 17 – 22, 2010.
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M. S Salam, D. Mohamad and S. H Salleh, “Insertion Reduction in Speech Segmentation Using Neural Network”, in Information Technology, 2008. ITSim International Symposium, Kuala Lumpur, 26-28 Aug. 2008, pp.no. 1-7.
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R. Sabah and R.N. Ainon, “Isolated Digit Speech Recognition in Malay Language Using Neuro-Fuzzy Approach”, in Modelling & Simulation, AMS '09. Third Asia International Conference , Bali, 25-29 May 2009, pp.no. 336 – 340.
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Department of Computer Graphics & Multimedia - Universiti Teknologi Malaysia (UTM)
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Universiti Teknologi Malaysia (UTM) Repository
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| M-S Salam : Colleagues
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| Dzulkifli Mohamad : Colleagues
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| S-H Salleh : Colleagues
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