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Densely Connected Networks with Multiple Features for Classifying Sound Signals with Reverberation

Densely Connected Networks with Multiple Features for Classifying Sound Signals with Reverberation

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8a5163d793a34ab3b9f68d55471ad0a4

Densely Connected Networks with Multiple Features for Classifying Sound Signals with Reverberation

About this item

Full title

Densely Connected Networks with Multiple Features for Classifying Sound Signals with Reverberation

Publisher

Basel: MDPI AG

Journal title

Sensors (Basel, Switzerland), 2023-08, Vol.23 (16), p.7225

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

In indoor environments, reverberation can distort the signalseceived by active noise cancelation devices, posing a challenge to sound classification. Therefore, we combined three speech spectral features based on different frequency scales into a densely connected network (DenseNet) to accomplish sound classification with reverberation effects. We...

Alternative Titles

Full title

Densely Connected Networks with Multiple Features for Classifying Sound Signals with Reverberation

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_8a5163d793a34ab3b9f68d55471ad0a4

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8a5163d793a34ab3b9f68d55471ad0a4

Other Identifiers

ISSN

1424-8220

E-ISSN

1424-8220

DOI

10.3390/s23167225

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