Speech intelligibility enhancement: a hybrid wiener approach

Abstract

Speech enhancement primarily focuses on improving the intelligibility and quality of the speech signal by using various algorithms and techniques. Processing of a speech signal refers to applying efficient mechanisms to reduce noise in the way of extracting the intended speech signal from the corrupted signal. Noise reduction techniques such as kalman filtering, spectral subtraction and adaptive wiener filtering etc. are used in different enhancement scenarios in speech processing. In the proposed method, the combination of wiener filter and Karhunen–Loeve Transform is used to remove noise and enhance the noisy speech signal. This paper presents the performance evaluation of the proposed hybrid algorithm by estimating Signal to Noise Ratio, Perceptual Evaluation of Speech Quality, Short-Time Objective Intelligibility and Extended STOI values. This algorithm has been implemented in varied noisy conditions and the results proved the fruitfulness of this method. Subjective listening evaluation is also done and both the objective and subjective results confirmed the significant improvement in speech intelligibility in the proposed method.