Szczegóły publikacji
Opis bibliograficzny
Causal signal-based DCCRN with overlapped-frame prediction for online speech enhancement / Julitta BARTOLEWSKA, Stanisław KACPRZAK, Konrad KOWALCZYK // W: INTERSPEECH 2023 [Dokument elektroniczny] : Dublin, Ireland, 20-24 August 2023 / [eds.] Naomi Harte, Julie Carson-Berndsen, Gareth Jones. — Wersja do Windows. — Dane tekstowe. — [France : ISCA], [2023]. — S. 4039–4043. — Wymagania systemowe: Adobe Reader. — Tryb dostępu: https://www.isca-speech.org/archive/pdfs/interspeech_2023/bar... [2023-09-19]. — Bibliogr. s. 4043, Abstr.
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 148720 |
|---|---|
| Data dodania do BaDAP | 2023-09-20 |
| DOI | 10.21437/Interspeech.2023-2177 |
| Rok publikacji | 2023 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | Interspeech 2023 |
Abstract
The aim of speech enhancement is to improve speech signal quality and intelligibility from a noisy microphone signal. In many applications, it is crucial to enable processing with small computational complexity and minimal requirements regarding access to future signal samples (look-ahead). This paper presents signal-based causal DCCRN that improves online single-channel speech enhancement by reducing the required look-ahead and the number of network parameters. The proposed modifications include complex filtering of the signal, application of overlapped-frame prediction, causal convolutions and deconvolutions, and modification of the loss function. Results of performed experiments indicate that the proposed model with overlapped signal prediction and additional adjustments, achieves similar or better performance than the original DCCRN in terms of various speech enhancement metrics, while it reduces the latency and network parameter number by around 30%.
