An Efficient Structured Sparsity Model For Reverberant Speech Separation - Sherikh K. K, Khamarunnisa P. , (International Journal of Engineering and Computer Science, 2015)
The growth of technology in this world is at a very high rate and hence the need to cope up with it is essential. In the field of communication, speech is one with the topmost priority. Performance of current speech recognition systems severely degrades in the presence of noise and reverberation. While rather simple and effective noise reduction techniques have been extensively applied, coping with reverberation still remains as one of the toughest problems in speech recognition and signal processing. Reverberation in speech is one of the primary factors which degrade the quality of the audio by persistence of audio in space by creating large number of echoes. Reverberation degrades the speech signal when recorded by a distant microphone and in the hands free telephonic scenarios. This reverberation corrupts the speech signal and it is difficult to carrying out communication in automatic voice recognition applications in which the voice is not properly recognized by the voice recognition applications. Reverberation in speech, caused by room reflections, is problematic especially for hands-free telephonic applications in a confined space. The problem is even severe for hearing impaired people. Therefore blind speech dereverberation is an important research area. The task is to remove reverberation from the output of a room, where the room impulse response, as well as the clean speech signal is unknown.