Investigation of Speech Intelligibility Using Artificial Neural Network Model

Abstract

A classroom acoustic is an important and difficult part of universityclassroom design. Good design is achieved more on the basis ofacoustics expertise than on pure engineering design. In this paper, theArtificial Neural Network (ANN) model is used for predicting speechintelligibility in classroom. There are several classroom properties such asdiminution of the class, signal to noise ratio (SNR), the location of thestudent and teacher , background noise where collected from theclassroom. A set of word is complied and a speech signal data base wascreated. The sound pressure levels are then measured using soundpressure meter at different classroom positions. A datasheet was obtainedfrom the measurement and then used to provide as training database intolearning process of (ANN) to predict the speech intelligibility at variouslisteners' position of classroom. This method improve high accuracy,efficiency and economic of calculation intelligibility in classrooms.Therefore it reduces the error by using the classic methods