[Show abstract][Hide abstract] ABSTRACT: The paper presents a new speech enhancement approach for a single channel speech enhancement in a noise environment. In this method speech is mixed with real-world noises from babble, car and street environments. In this paper we proposed modified Kalman method for effective speech enhancement. The proposed method is compared to the traditional Spectral Subtraction (SS), Wiener Filter (WF), Minimum Mean Square Error (MMSE) and Wavelet based Filter (WAVELET). Experiments showed that the modified algorithm can give better SNR improvement and Subjective evaluation tests demonstrate significant improvement results over classical algorithms, when tested withspeech signal corrupted a posterior by various noises at different signal to noise ratios.
[Show abstract][Hide abstract] ABSTRACT: Animals produce different sounds for their communication. Animal voices collected under normal environmental conditions are usually degraded due to noise and distortion. “Speech enhancement” is an attempt to improve the degraded voice quality while preserving the information, at the very least, speech intelligibility. The objective of speech enhancement algorithms is to improve one or more perceptualaspects of noisy speech, most notably, and quality. The species under evaluation are African elephant, Beluga whale, and Ortolan bunting. The paper presents a fine approach for speech enhancement over the recordings of selected animal vocalizations in noisy environments. The proposed approach is evaluated by selected algorithms used ndividually as well as cascaded combinations for a better signal to noise ratio. The noise reduction algorithms under investigation in this paper are the Spectral Subtraction (SS), Wiener Filter (WF), Minimum Mean Square Error (MMSE), Wavelet based Filter (WT), and Kalman Filter (KF).