RT Journal Article
T1 Auditory-inspired morphological processing of speech spectrograms: applications in automatic speech recognition and speech enhancement
A1 Cadore, Joyner
A1 Valverde Albacete, Francisco José
A1 Gallardo Antolín, Ascensión
A1 Peláez Moreno, Carmen
AB New auditory-inspired speech processing methods are presented in this paper, combining spectral subtraction and two-dimensional non-linear filtering techniques originally conceived for image processing purposes. In particular, mathematical morphology operations, like erosion and dilation, are applied to noisy speech spectrograms using specifically designed structuring elements inspired in the masking properties of the human auditory system. This is effectively complemented with a pre-processing stage including the conventional spectral subtraction procedure and auditory filterbanks. These methods were tested in both speech enhancement and automatic speech recognition tasks. For the first, time-frequency anisotropic structuring elements over grey-scale spectrograms were found to provide a better perceptual quality than isotropic ones, revealing themselves as more appropriate—under a number of perceptual quality estimation measures and several signal-to-noise ratios on the Aurora database—for retaining the structure of speech while removing background noise. For the second, the combination of Spectral Subtraction and auditory-inspired Morphological Filtering was found to improve recognition rates in a noise-contaminated version of the Isolet database.
PB Springer
SN 1866-9956 (Print)
SN 1866-9964 (Online)
YR 2012
FD 2012-11
LK https://hdl.handle.net/10016/15932
UL https://hdl.handle.net/10016/15932
LA eng
NO This work has been partially supported by the Spanish Ministry of Science and Innovation CICYT Project No. TEC2008-06382/TEC.
DS e-Archivo
RD 3 jun. 2024