Modulation and performance of synchronous demodulation for speech signal detection and dialect intelligibility

Abstract

Abstract Speech processing is one of the fundamental operations in computer science and it is particularly difficult to process and distinguish speech in different Arabic dialects when background noise is present. In any nation, communication skills are crucial. Pushing a button is all it takes for the typical person to make phone calls and leave voicemails but for telecommunications experts, the process is very different. We understand how communication actually works. The terms detection and demodulation are commonly used when addressing the full demodulation process. The procedures and circuits are substantially the same under both designations. As the name implies, demodulation is the opposite of modulation, which is applying a signal, such as an audio signal, to a carrier. The demodulation process isolates the output signal from the audio or other signal that was transmitted using amplitude shifts on the carrier. In this study, a system for distinguishing speech signals was developed using modulation and demodulation to transmit speech by extracting it from a variety of factors, the most significant of which is background noise in addition to a wide variety of dialects, which poses a significant challenge in speech processing. The proposed system was applied to a dataset that was created for a group of voices in different dialects, and by using important techniques, the noise accompanying the voices was deleted and then the voices were processed with other techniques such as modulation and demodulation to distinguish the dialect. The system has proven effective by distinguishing dialects.