… the robustness of our techniques to noise will allow for a better form of speech recognition. …
for resolving noisy signals was put forth by [5] using a filtered-correlation fractal dimension …

… as an accumulated change of signal values, and d as a dynamic range of the speech signal.
… a suboptimal feature filtering approach to eliminate redundant, irrelevant or noisy features. …

… of dynamics. 20 Although there are many algorithms for calculating the fractal dimension,
none … 50 Therefore, we apply the geometrically based filters on the phase space to identify the …

… and Dynamic Time Warping (DTW) for implementing a noise-resilient speech recognition
system … Pre-emphasis filtering, noise thresholding, and zero alignment techniques are used to …

… The speech analysis part of the speech recognition system … Taking into account these
successful fractal dimension features-… The number of filters used in this research is equal to 128. …

… by extracting the fractal dimension features in natural speech [9, 10]. … noise cancellation
performance for speech recognition but … of speech on the recognition results, this paper filters the …

… the speech signals for emotion recognition. The emotional arousal of a speaker is reflected in
the speech, which in turn is reflected in spectral dynamics … speech recognition in noise [85]. …

… filtering the non-pre-emphasized speech … speech, and silence and noise as non-speech
[4]. VAD is also used in a number of speech technology applications such as speech recognition …

… filter banks) approaches to learning filters as part of the network. … the noise ratio as the 0.005
× max value in the speech signal… of speech processing, such as speech recognition, speech …

… the noisy input speech signal in the DFT domain. Especially, Kalman filter is used for filtering
and modeling the temporal trajectories of noisy … A dynamic role of windowing and framing …