Jeevan Reddy Yarragudi , pp. 54. ING/School of Engineering, 2012.
A major part of the interaction between humans takes place via speech communication. It is very difficult to understand speech signals in presence of background noise for the normal listeners and hearing impaired persons. The human speech and hearing organ is inherently sensitive to interfering noise. Interfering noise decreases speech intelligibility and quality. Speech enhancement algorithms reduces the noise and improve one or more perceptual aspects of noisy speech most notably quality and intelligibility. The main objective of speech enhancement is to reduce the influence of the noise. Speech communication is processing through Tele-conferencing, audio conferencing and video conferencing, these are influenced in indoors, office environments and closed auditoriums i.e. communication between one person to another person. These communication systems will become disturbing by some unknown noises like random noises, some mobile ring disturbances and fan noises in computers. The quality of speech is reduced in indoors due to the propagation channel (medium) and additional noise sources. According to these disturbances the quality of original speech is de-graded in conservations, so it’s need to enhance the speech from the noisy environment.
In this thesis work, first proposing appropriate microphone array setup with improved speech processing technique, and implementing the generalized side lobe canceller (GSC) beam forming techniques by using required adaptive algorithm (LMS). In order to get better speech quality using the Microphone arrays. Microphone arrays have been widely used to improve the performance of speech recognition systems as well as to benefit for people who need having aids. With the help of microphone arrays, it can choose to focus on signals from a specific direction. To getting better speech quality in microphone array using adaptive algorithms, these are help in the noise suppression in accordance with the different beam forming techniques.
The proposed system is implemented and evaluated using MATLAB simulation tool. The objective quality measures is Signal to Noise Ratio Improvement (SNRI), is using to validate the system. The systems were tested with a pure speech combination of male and female sampled at16 KHz, one interference noise is the male voice sampled at 16KHz and one random noises are simulated at different positions of speech and noise sources with different input SNR ratios of 0dB, 5dB, 10dB, 15dB, 20dB and 25dB. The overall signal to noise ratio improvement is determined from the main speech and two noise inputs and output powers. The SNR improvement at wiener beam former system is around 20dB and the SNR improvement at GSC system is around 26dB.