Nov 10, 2021 · Intelligibility of speech can be significantly reduced when it is presented in adverse near-end listening conditions, like background noise.

Abstract—Intelligibility of speech can be significantly reduced when it is presented in adverse near-end listening conditions, like background noise.

A DNN-based model that generates a talking face from speech audio can meaningfully enhance comprehension in noisy environments.

Mar 22, 2022 · To address the full-end speech enhancement task where both speaker and listener environments are noisy, we proposed a. DNN-based joint framework ...

These investigations have demonstrated that modifications which successfully promote intelligibility can also have the side effect of reducing speech quality [ ...

Oct 13, 2022 · In this paper, we present resource-efficient and compact neural models for end-to-end noise-robust waveform-based speech enhancement.

The results show that the proposed algorithm achieves better speech intelligibility and quality. Besides, less residual noise and speech distortion is observed.

In recent years, a range of algorithms has been developed to enhance the intelligibility of speech rendered in a noisy environment. We describe methods ... [ ...

Jun 9, 2024 · Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users. Hear. Res. 344, 183–194 ...

Oct 25, 2023 · In this paper, we review the current DNN techniques being employed to achieve speech enhancement and separation.