title: The robustness of speech representations obtained from simulated auditory nerve fibers under different noise conditions.
abstract: Different methods of extracting speech features from an auditory model were systematically investigated in terms of their robustness to different noises. The methods either computed the average firing rate within frequency channels (spectral features) or inter-spike-intervals (timing features) from the simulated auditory nerve response. When used as the front-end for an automatic speech recognizer, timing features outperformed spectral features in Gaussian noise. However, this advantage was lost in babble, because timing features extracted the spectro-temporal structure of babble noise, which is similar to the target speaker. This suggests that different feature extraction methods are optimal depending on the background noise.
authors: Cluster of Excellence Hearing4all, Department of Medical Physics und Acoustics, Carl-von-Ossietzky Universität Oldenburg, 26111 Oldenburg, Germany. tim.juergens@uni-oldenburg.de
authors: Tim
authors: T
authors: Jürgens
authors: Thomas
authors: T
authors: Brand
authors: Nicholas R
authors: NR
authors: Clark
authors: Ray
authors: R
authors: Meddis
authors: Guy J
authors: GJ
authors: Brown
mesh_terms: D003056:Cochlear Nerve / Q000502:physiology*; D003198:Computer Simulation; D005583:Fourier Analysis; D006801:Humans; D008959:Models, Neurological; D009622:Noise; D010363:Pattern Recognition, Automated; D059629:Signal-To-Noise Ratio; D013018:Sound Spectrography; D013061:Speech Acoustics; D013068:Speech Production Measurement / Q000379:methods; D049250:Speech Recognition Software; D013997:Time Factors