Publication Details
SdSV Challenge 2020: Large-Scale Evaluation of Short-duration Speaker Verification
Speaker Recognition, Benchmark, Shortduration, Evaluation
Modern approaches to speaker verification represent speech utterances as fixed-length embeddings. With these approaches, we implicitly assume that speaker characteristics are independent of the spoken content. Such an assumption generally holds when sufficiently long utterances are given. In this context, speaker embeddings, like i-vector and x-vector, have shown to be extremely effective. For speech utterances of short duration (in the order of a few seconds), speaker embeddings have shown significant dependency on the phonetic content. In this regard, the SdSV Challenge 2020 was organized with a broad focus on systematic benchmark and analysis on varying degrees of phonetic variability on short-duration speaker verification (SdSV). In addition to text-dependent and text-independent tasks, the challenge features an unusual and difficult task of cross-lingual speaker verification (English vs. Persian). This paper describes the dataset and tasks, the evaluation rules and protocols, the performance metric, baseline systems, and challenge results. We also present insights gained from the evaluation and future research directions.
@inproceedings{BUT168146,
author="ZEINALI, H. and LEE, K. and ALAM, J. and BURGET, L.",
title="SdSV Challenge 2020: Large-Scale Evaluation of Short-duration Speaker Verification",
booktitle="Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",
year="2020",
journal="Proceedings of Interspeech",
volume="2020",
number="10",
pages="731--735",
publisher="International Speech Communication Association",
address="Shanghai",
doi="10.21437/Interspeech.2020-1485",
issn="1990-9772",
url="https://www.isca-speech.org/archive/Interspeech_2020/pdfs/1485.pdf"
}