Download Regional Conference on Science, Technology and Social by Nor Azizah Yacob, Mesliza Mohamed, Megat Ahmad Kamal Megat PDF

By Nor Azizah Yacob, Mesliza Mohamed, Megat Ahmad Kamal Megat Hanafiah

This e-book gathers chosen technology and know-how papers that have been awarded on the 2014 local convention of Sciences, know-how and Social Sciences (RCSTSS 2014). The bi-annual convention is equipped by way of Universiti Teknologi MARA Pahang, Malaysia. The papers deal with a vast variety of issues together with structure, existence sciences, robotics, sustainable improvement, engineering, nutrition technological know-how and arithmetic. The booklet serves as a platform for disseminating examine findings, as a catalyst to encourage optimistic concepts within the improvement of the zone.
The carefully-reviewed papers during this quantity current examine via academicians of neighborhood, nearby and international prominence. Out of greater than two hundred manuscripts offered on the convention by way of researchers from neighborhood and overseas universities and associations of upper studying, sixty four papers have been selected for inclusion during this booklet. The papers are equipped in additional than a dozen wide different types, spanning the diversity of medical research:
• Engineering• Robotics• arithmetic & records• desktop & details know-how• Forestry• Plantation & Agrotechnology• activities technological know-how & sport• overall healthiness & medication• Biology• Physics• foodstuff technological know-how• surroundings technological know-how & administration• Sustainable improvement• structure
The publication offers an important element of reference for lecturers, researchers and scholars in lots of fields who desire deeper research.

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Procedia Engineering 64(2013):385–394. 111 Yusnita MA, Paulraj MP, Yaacob S, Yusuf R, Shahriman AB (2013b) Analysis of accent-sensitive words in multi-resolution mel-frequency cepstral coefficients for classification of accents in Malaysian english. Int J Automot Mech Eng 7(2013):1053–1073 Chapter 5 Robustness Analysis of Feature Extractors for Ethnic Identification of Malaysian English Accents Database Mohd Ali Yusnita, Murugesa Pandiyan Paulraj, Sazali Yaacob, Abu Bakar Shahriman, Rihana Yusuf and Mokhtar Nor Fadzilah Abstract Accent is fascinating human speech behavior that can be used to mark personal identity and social characteristics of its bearer.

4 concludes the important findings and investigation of this paper. 2 Methodology Speech Database and Experimental Setup For the purpose of this research, a new MalE accents database was developed by conducting a series of recording sessions in a semi-anechoic acoustic chamber using a handheld condenser, supercardioid and unidirectional microphone using a laptop computer sound card and MATLAB program. The recorded background noise level in the chamber was 22 dB. The sampling rate and bit resolution were set to 16 kHz and 16 bps for normal high quality used in automatic speech recognition applications.

Instead, this paper presents experimental methods by means of acoustical analysis and machine learning techniques. In order to enhance the performance of accent classifier to classify the Malay, Chinese, and Indian accents this paper proposes fusion techniques of popularly known mel-frequency cepstral coefficients (MFCC) and linear prediction coefficients (LPC) with formants termed here as spectral feature fusions (SFFs). In these SFFs feature extractors, the main spectral features are fused with five usable formants and the extracted features are used to model K-nearest neighbors and artificial neural networks (ANN).

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