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Title: | Prediction of classroom speech clarity using backpropagation neural network |
Authors: | Paularaj, M. P. Sazali, Yaacob Ahmad Nazri Thagirarani, M |
Keywords: | Neural network model Speech clarity Speech intelligibility Reverberation time Signal to noise ration Neural networks (Computer science) Back propagation |
Issue Date: | 27-Nov-2007 |
Publisher: | Universiti Kebangsaan Malaysia |
Series/Report no.: | Proceeding of Regional Conference on Engineering Mathematics, Mechanics, Manufacturing & Architecture (EM3ARC 2007) |
Abstract: | A classroom's acoustic design should be constructed so that the highest possible degree of speech intelligibility is achieved for teachers and students. In achieving the highest possible speech intelligibility, the acoustical design of classrooms should be based on the listener's positions in the classroom. The variation of Speech Clarity (SC) in a University Classroom with respect to Signal to Noise Ratio (SN) is dealt in this paper. The speech levels are measured at different seating position and the SC is determined. A simple Neural Network model was developed to predict the SC at any point in the classroom. |
Description: | Organized by Fakulti Kejuruteraan, Universiti Kebangsaan Malaysia, 27th - 28th November 2007 at Kuala Lumpur. |
URI: | http://dspace.unimap.edu.my/123456789/6368 |
Appears in Collections: | Conference Papers Sazali Yaacob, Prof. Dr. |
Files in This Item:
File | Description | Size | Format | |
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Prediction Of Classroom Speech Clarity Using Backpropagation Neural Network.pdf | Access is limited to UniMAP community. | 4.48 MB | Adobe PDF | View/Open |
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