Nonlinear dynamics approach to speech detection in noisy signals
Łukasz Bronakowski · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
The presented paper describes a novel approach to detection of speech corrupted by noise. The proposed procedure is based on fractal dimension, which is being evaluated directly from speech signal samples using two different methods: box-counting and the approach proposed by Katz. The recordings, taken from TIMIT database, were corrupted by five different types of noise (white, pink, hf-channel, babble and factory) with four noise amplitudes (5,10,15,20 dB). The resulting noisy speech was the subject of the analysis. The Otsu's method was used to determine a threshold value for differentiating between noise-only and noisy-speech segments. It has been shown that fractal dimension-based approach provides good basis for detecting speech under a presence of noise.