Abstract:
Communication between computer and
human has become increasingly popular in today
world. Investigation of human emotion importance is
also growing in several domains. But under real
world condition, speech signal is often, corrupted
with several noise types and the accuracy of
recognition is degraded from these noisy signal.
Therefore this paper focuses on the speech
enhancement techniques to develop emotion
recognition system for the noisy signal in the real
world environment. The various popular
enhancement techniques are analyzed by adding the
background noise to the clean signal using various
SNR. To test the accuracy of the system, the widely
used MFCC signal features are against with the SVM
classifier. Results after enhancing were compared to
that noisy signal and that clean signal to measure the
system performance. The experimental results show
the best performance algorithm and all enhancement
algorithms improve the emotion recognition system
performance under various SNRs level of real world
background noise.
