Single-channel speech enhancement by PSO-GSA with harmonic regeneration noise reduction

Abstract

Speech quality significantly affects the performance of speech dependent systems. Noise in the background lowers the clarity and intelligibility of speech. The augmentation of speech can increase its quality. We propose a single-channel speech improvement framework that combines particle swarm optimization (PSO), gravitational search algorithm (GSA), and harmonic regeneration noise reduction (HRNR) to minimize speech signal noise and increase speech intelligibility. The proposed hybrid algorithm optimizes the amount of overlap between the noisy speech frames. This helps in reducing the overlapped noise. Then HRNR algorithm is applied to retain the speech harmonics. The algorithm gives improvement in the speech intelligibility for babble, car and exhibition noise. The segmental signal to noise ratio (SNR) is also improved for these noise types. There is improvement in speech intelligibility with minimal speech distortion.