Environment Classification via Blind Roomprints Estimation

Autor:	Malte Baum, Luca Cuccovillo, Artem Yaroshchuk, Patrick Aichroth
Rok vydání:	2022
Předmět:	FOS: Computer and information sciences Sound (cs.SD) Audio and Speech Processing (eess.AS) FOS: Electrical engineering electronic engineering information engineering Computer Science - Sound Electrical Engineering and Systems Science - Audio and Speech Processing
DOI:	10.48550/arxiv.2209.07196
Popis:	In this paper we present a novel approach for environment classification for speech recordings, which does not require the selection of decaying reverberation tails. It is based on a multi-band RT60 analysis of blind channel estimates and achieves an accuracy of up to 93.6% on test recordings derived from the ACE corpus.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::387d353dc8fb9ea100f287aaa9580a17 Zobrazit plný text záznamu