4 accepted papers
Conventional deep neural network (DNN)-based speech enhancement (SE) approaches aim to minimize the mean square error (MSE) between enhanced speech and clean reference. The MSE-optimized model may not directly improve the performance of an automatic speech recognition (ASR) system. If the target is…
Reverberation, which is generally caused by sound reflections from walls, ceilings, and floors, can result in severe performance degradation of acoustic applications. Due to a complicated combination of attenuation and time-delay effects, the reverberation property is difficult to characterize, and…
This paper presents a novel postfiltering approach based on the locally linear embedding (LLE) algorithm for speech enchantment (SE). The aim of the proposed LLE-based postfiltering approach is to further remove the residual noise components from the SE-processed speech signals through a spectral co…
For hearing aid (HA) devices, speech enhancement (SE) is an essential unit aiming to improve signal-to-noise ratio (SNR) and quality of speech signals. Previous studies, however, indicated that user experience with current HAs was not fully satisfactory in noisy environments, suggesting that there i…