ICSpk: Interpretable Complex Speaker Embedding Extractor from Raw Waveform
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F21%3APU142958" target="_blank" >RIV/00216305:26230/21:PU142958 - isvavai.cz</a>
Result on the web
<a href="https://www.isca-speech.org/archive/interspeech_2021/peng21_interspeech.html" target="_blank" >https://www.isca-speech.org/archive/interspeech_2021/peng21_interspeech.html</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.21437/Interspeech.2021-2016" target="_blank" >10.21437/Interspeech.2021-2016</a>
Alternative languages
Result language
angličtina
Original language name
ICSpk: Interpretable Complex Speaker Embedding Extractor from Raw Waveform
Original language description
Recently, extracting speaker embedding directly from raw waveform has drawn increasing attention in the field of speaker verification. Parametric real-valued filters in the first convolutional layer are learned to transform the waveform into time-frequency representations. However, these methods only focus on the magnitude spectrum and the poor interpretability of the learned filters limits the performance. In this paper, we propose a complex speaker embedding extractor, named ICSpk, with higher interpretability and fewer parameters. Specifically, at first, to quantify the speaker-related frequency response of waveform, we modify the original short-term Fourier transform filters into a family of complex exponential filters, named interpretable complex (IC) filters. Each IC filter is confined by a complex exponential filter parameterized by frequency. Then, a deep complex-valued speaker embedding extractor is designed to operate on the complex-valued output of IC filters. The proposed ICSpk is evaluated onVoxCeleb andCNCeleb databases. Experimental results demonstrate the IC filters-based system exhibits a significant improvement over the complex spectrogram based systems. Furthermore, the proposed ICSpk outperforms existing raw waveform based systems by a large margin.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
ISBN
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ISSN
1990-9772
e-ISSN
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Number of pages
5
Pages from-to
511-515
Publisher name
International Speech Communication Association
Place of publication
Brno
Event location
Brno
Event date
Aug 30, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000841879500103