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Detail publikačního výsledku
ONDEL YANG, L.; LI, R.; SELL, G.; HEŘMANSKÝ, H.
Originální název
Deriving Spectro-temporal Properties of Hearing from Speech Data
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
Human hearing and human speech are intrinsically tied together, asthe properties of speech almost certainly developed in order to beheard by human ears. As a result of this connection, it has beenshown that certain properties of human hearing are mimicked withindata-driven systems that are trained to understand human speech.In this paper, we further explore this phenomenon by measuring thespectro-temporal responses of data-derived filters in a front-end convolutionallayer of a deep network trained to classify the phonemesof clean speech. The analyses show that the filters do indeed exhibitspectro-temporal responses similar to those measured in mammals,and also that the filters exhibit an additional level of frequency selectivity,similar to the processing pipeline assumed within the ArticulationIndex.
Anglický abstrakt
Klíčová slova
perception, spectro-temporal, auditory, deeplearning
Klíčová slova v angličtině
Autoři
Rok RIV
2020
Vydáno
12.05.2019
Nakladatel
IEEE Signal Processing Society
Místo
Brighton
ISBN
978-1-5386-4658-8
Kniha
Proceedings of ICASSP
Strany od
411
Strany do
415
Strany počet
5
URL
https://ieeexplore.ieee.org/document/8682787
BibTex
@inproceedings{BUT160004, author="ONDEL YANG, L. and LI, R. and SELL, G. and HEŘMANSKÝ, H.", title="Deriving Spectro-temporal Properties of Hearing from Speech Data", booktitle="Proceedings of ICASSP", year="2019", pages="411--415", publisher="IEEE Signal Processing Society", address="Brighton", doi="10.1109/ICASSP.2019.8682787", isbn="978-1-5386-4658-8", url="https://ieeexplore.ieee.org/document/8682787" }
Dokumenty
ondel_icassp2019_08682787