Year: 2025
Type: conference-paper
Abstract: In this paper, we investigate the influence of language similarity in cross-lingual non-target speaker verification trials using a state-of-the-art speaker verification system, ECAPA-TDNN, trained on multilingual and monolingual variants of the VoxCeleb dataset. Our analysis of the score distribution patterns on multilingual Globalphone and LDC CTS reveals a clustering effect in speaker comparisons involving a training language, whereby the choice of comparison language only minimally impacts scores. Conversely, we observe a language similarity effect in trials involving languages not included in the training set of the speaker verification system, with scores correlating with language similarity measured by a language classification system, especially when using multilingual training data.
Source: Interspeech (USB)
Authors: Paul M. Reuter, Michael Jessen
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4415433947
FWCI:
Cites:
Cited by:
Related to: