Cuckoo search based optimal mask generation for noise suppression and enhancement of speech signal

Abstract

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 experimentation of the proposed technique was carried out using various datasets and the performance is compared with the previous techniques using SNR. The results obtained proved the effectiveness of the proposed technique and its ability to suppress noise and enhance the speech signal.

Keywords

• Noise suppression
• Enhancement of speech signal
• AMS feature extraction
• Cuckoo search
• Waveform synthesis
• Optimal mask