Abstract

The main objective of this study is to have the noise component of a speech signal eliminated and compressed by storing the locations and durations of silence regions. The separation between voiced, unvoiced, and silence regions is done by using the Short-Time Energy (STE) and Zero Crossing Rate (ZCR) methodologies. All operations in this study have been performed by using the User Interface (UI) developed on MATLAB®. These operations include voice recording, playing the recording, eliminating the unwanted regions, playing the modified recording, saving original and compressed files, and loading the recording compressed.

Highlights

  • A typical voice recording consists of three main regions: Voiced regions where the speech of interest is mainly stored on, unvoiced regions which contains the low amplitude sections from the source that is unrecognizable, and the silence parts which only contain the unwanted noise

  • The process is started by the user with recording

  • After recording step has been performed, the original speech waveform can be obtained as seen in Figure 1. 2.1

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Summary

Introduction

A typical voice recording consists of three main regions: Voiced regions where the speech of interest is mainly stored on, unvoiced regions which contains the low amplitude sections from the source that is unrecognizable, and the silence parts which only contain the unwanted noise. Main objective of this study is to separate and eliminate the unvoiced and silence regions and compress the speech signal. The locations and durations of these signal parts will be stored for the reconstruction purpose . This study includes developing a User Interface (UI) created on MATLAB®.

Objectives
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