Speech signal quality improvement attempt to attenuate ambient noise to reduce listener fatigue and improve intelligibility. This requires maintaining speech cues and ensuring natural sounding residual noise that does not distract the listener. In this paper, an effective noise suppression technique for enhancement of speech signals using optimized mask is proposed. Initially, the noisy speech signal is broken down into various time-frequency (TF) units and the features are extracted by finding out the Amplitude Magnitude Spectrogram (AMS). The signals are then classified based on quality ratio into different classes to generate the initial set of solutions. Subsequently, the optimal mask for each class is generated based on Cuckoo search algorithm. Subsequently, in the waveform synthesis stage, filtered waveforms are windowed and then multiplied by the optimal mask value and summed up to get the enhanced target signal. The results obtained proved the effectiveness of the proposed technique and is able to suppress noise and improve the quality of the speech signal.

Full text: IJEIR_743_Final.pdf