The INTERSPEECH 2020 Far-Field Speaker Verification Challenge
Abstract
The INTERSPEECH 2020 Far-Field Speaker Verification Challenge (FFSVC 2020) addresses three different research problems under well-defined conditions: far-field text-dependent speaker verification from single microphone array, far-field text-independent speaker verification from single microphone array, and far-field text-dependent speaker verification from distributed microphone arrays. All three tasks pose a cross-channel challenge to the participants. To simulate the real-life scenario, the enrollment utterances are recorded from close-talk cellphone, while the test utterances are recorded from the far-field microphone arrays. In this paper, we describe the database, the challenge, and the baseline system, which is based on a ResNet-based deep speaker network with cosine similarity scoring. For a given utterance, the speaker embeddings of different channels are equally averaged as the final embedding. The baseline system achieves minDCFs of 0.62, 0.66, and 0.64 and EERs of 6.27%, 6.55%, and 7.18% for task 1, task 2, and task 3, respectively.
Keywords
Cite
@article{arxiv.2005.08046,
title = {The INTERSPEECH 2020 Far-Field Speaker Verification Challenge},
author = {Xiaoyi Qin and Ming Li and Hui Bu and Wei Rao and Rohan Kumar Das and Shrikanth Narayanan and Haizhou Li},
journal= {arXiv preprint arXiv:2005.08046},
year = {2020}
}
Comments
Submitted to INTERSPEECH 2020