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STAFYLAKIS, T. ROHDIN, J. BURGET, L.
Originální název
Speaker embeddings by modeling channel-wise correlations
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Speaker embeddings extracted with deep 2D convolutional neural networks are typically modeled as projections of first and second order statistics of channel-frequency pairs onto a linear layer, using either average or attentive pooling along the time axis. In this paper we examine an alternative pooling method, where pairwise correlations between channels for given frequencies are used as statistics. The method is inspired by style-transfer methods in computer vision, where the style of an image, modeled by the matrix of channel-wise correlations, is transferred to another image, in order to produce a new image having the style of the first and the content of the second. By drawing analogies between image style and speaker characteristics, and between image content and phonetic sequence, we explore the use of such channel-wise correlations features to train a ResNet architecture in an end-to-end fashion. Our experiments on VoxCeleb demonstrate the effectiveness of the proposed pooling method in speaker recognition.
Klíčová slova
speaker recognition, style-transfer, deep learning
Autoři
STAFYLAKIS, T.; ROHDIN, J.; BURGET, L.
Vydáno
30. 8. 2021
Nakladatel
International Speech Communication Association
Místo
Brno
ISSN
1990-9772
Periodikum
Proceedings of Interspeech
Ročník
2021
Číslo
8
Stát
Francouzská republika
Strany od
501
Strany do
505
Strany počet
5
URL
https://www.isca-speech.org/archive/interspeech_2021/stafylakis21_interspeech.html
BibTex
@inproceedings{BUT175834, author="Themos {Stafylakis} and Johan Andréas {Rohdin} and Lukáš {Burget}", title="Speaker embeddings by modeling channel-wise correlations", booktitle="Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH", year="2021", journal="Proceedings of Interspeech", volume="2021", number="8", pages="501--505", publisher="International Speech Communication Association", address="Brno", doi="10.21437/Interspeech.2021-1442", issn="1990-9772", url="https://www.isca-speech.org/archive/interspeech_2021/stafylakis21_interspeech.html" }