In recent decades, keystroke suppression has got a particular attention due to the increasing use of laptops and computers to capture audio in various communication scenarios such as meetings, audio/video instant messaging etc. In many of these situations, a unique problem of additive keystroke transient noise is faced. Because of the non-stationary, short time and abrupt nature of the keystroke transient, it has been a challenging task for many years. In this paper, two new two-stage approaches for the suppression of keystrokes are proposed. In the first stage the speech is estimated using supervised sparse non-negative factorization, which is common in both of the methods. Then, in the second stage, keystrokes are detected and are suppressed by replacing the corrupted speech frames with the corresponding estimated speech frames obtained in the first stage using two new techniques, which is the core contribution of this work. Experimental results show that the proposed approaches exhibit good performance without significantly degrading the quality of speech.

Single channel speech enhancement short time Fourier transform supervised sparse non-negative matrix factorization correlation keystrokes suppression thresholding technique.