Publication Details
Analyzing speaker verification embedding extractors and back-ends under language and channel mismatch
Stafylakis Themos (OMILIA)
Mošner Ladislav, Ing. (DCGM FIT BUT)
Plchot Oldřich, Ing., Ph.D. (DCGM FIT BUT)
Rohdin Johan A., Dr. (DCGM FIT BUT)
Matějka Pavel, Ing., Ph.D. (DCGM FIT BUT)
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT)
Glembek Ondřej, Ing., Ph.D. (DCGM FIT BUT)
Brummer Johan Nikolaas Langenhoven, Dr. (Phonexia)
speaker, verification, embedding
In this paper, we analyze the behavior and performance of speaker embeddings and the back-end scoring model under domain and language mismatch. We present our findings regarding ResNet-based speaker embedding architectures and show that reduced temporal stride yields improved performance. We then consider a PLDA back-end and show how a combination of small speaker subspace, language-dependent PLDA mixture, and nuisance-attribute projection can have a drastic impact on the performance of the system. Besides, we present an efficient way of scoring and fusing class posterior logit vectors recently shown to perform well on speaker verification task. The experiments are performed using the NIST SRE 2021 setup.
@INPROCEEDINGS{FITPUB12834, author = "Anna Silnova and Themos Stafylakis and Ladislav Mo\v{s}ner and Old\v{r}ich Plchot and A. Johan Rohdin and Pavel Mat\v{e}jka and Luk\'{a}\v{s} Burget and Ond\v{r}ej Glembek and Langenhoven Nikolaas Johan Brummer", title = "Analyzing speaker verification embedding extractors and back-ends under language and channel mismatch", pages = "9--16", booktitle = "Proceedings of The Speaker and Language Recognition Workshop (Odyssey 2022)", year = 2022, location = "Beijing, CN", publisher = "International Speech Communication Association", doi = "10.21437/Odyssey.2022-2", language = "english", url = "https://www.fit.vut.cz/research/publication/12834" }