Removal of Typed Keystrokes from Speech Signals

Laptop computers are increasingly being used as recording devices

to capture meetings, interviews, and lectures using the laptop’s local

microphone. In these scenarios, the user frequently also uses

the same laptop to make notes. Because of the close proximity of

the laptop’s microphone to its keyboard, the captured speech signal

is significantly corrupted by the impulsive sounds the user’s

keystrokes generate. In this paper we propose an algorithm to automatically

detect and remove keystrokes from a recorded speech

signal. The detection and removal stages both operate by exploiting

the natural correlations present in speech signals, but do so in

different ways. The proposed algorithm is computationally efficient,

requires no user-specific training or enrollment, and results

in significantly enhanced speech. The proposed keystroke removal

algorithm was evaluated through user listening tests and speech

recognition experiments on speech recordings made in a realistic


PDF file

In  Proc. of the Interspeech Conference

Publisher  International Speech Communication Association
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