Novel frequency masking curves for noise-robust automatic speech recognition
Chia-Ping Chen, Ja-Zang Yeh, Bofeng Wu · Journal of the Chinese Institute of Engineers · 2012
We investigate the incorporation of frequency masking curves in the feature extraction module of automatic speech recognition systems to improve noise robustness. Frequency-masking curves are mathematically derived based on an auditory model, in which a basilar membrane is modeled as a cascade system of damped simple harmonic oscillators. Based on the analysis of the motion under speech signals, we derive the relationship between the amplitudes of neighboring oscillators and convert it into frequency-masking curves, which are used in the computation of spectral-masking thresholds to modify the speech spectrum. Evaluated on the Aurora 2.0 noisy-digit speech database, the proposed methodology achieves a significant improvement in noise-robustness.