Voice Extraction from Background Noise using Filter Bank Analysis for Voice Communication Applications

TLDR: In this paper, the authors applied prevalent feature extraction techniques to extract the speech signal with the trade off of complexity, compression ratio, and compression ratio for the application of voice communication.

Abstract: Automatic Speech Recognition plays an evident role in extracting the voice signal in the noisy background. The reduction of noise in the signal is susceptible to the information which is to be transmitted since not all the information is emphasized. This leads to the deterioration in the transmitted information and paved furtherance for automatic speech recognition. Prevalent feature extraction techniques are applied to extract the speech signal with the trade off of complexity, compression ratio. For the application of voice communication, filter bank analysis is applied to extract the voice signals in the noisy environment. This work emphasized on the attributes of the perceptual quality of Loudness, Pitch Intensity, Timing. Band pass filtering provides reliable extraction of the voice signal features in the noisy environment. The power distribution of the extracted signals for the selected audio signal with the length of more than 20 seconds wave file with a sampling rate of 16 Khz along with the background noises has been plotted and its respective spectrogram also been plotted.