… to understand speech in situations with background noise. Here, we present a deep
learning-based algorithm that selectively suppresses noise while maintaining speech signals. The …

… In deep learning, a common approach is to supply large amounts of low-level … let the DNN
learn the relevant high-level representations required to correctly recognize speech. Indeed, …

… deep learning–based NR approach used in this study consists of two modules: noise classifier
(NC) and deep … Moreover, we evaluate the speech recognition performance of the NC + …

… segregation has been shown to improve human speech intelligibility in noisy environments.
… speech intelligibility for hearing-impaired (HI) listeners. In the current study, a deep learning …

… deep learning-based non-intrusive speech intelligibility assessment model, namely STOI-Net.
The input and output of STOI-Net are speech … noisy and enhanced speech utterances. The …

… achieving large improvements in estimated speech quality (SQ) and speech intelligibility (SI), …
His main research interests include speech enhancement, deep learning, and intelligibility …

… STOI is a widely used objective measure of speech intelligibility, which is based on the
acoustic signals and correlates well to NH human performance. It essentially represents a …

… Deep learning based speech separation or noise reduction needs to generalize to voices
not encountered during training and to operate under multiple corruptions. The current study …

… This paper proposes a deep learning-based non-intrusive objective speech intelligibility …
is the standard intrusive intelligibility estimation method with reference speech signal. The input …

… units of ”normal” speech thanks to deep learning based system … this deep learning modeling
into a prediction task of intelligibility typically in the context of normal and disordered speech …