Stacked causal convolutional autoencoder based speech compression method
| dc.contributor.author | Bekiryazici, Tahir | |
| dc.contributor.author | Aydemir, Gurkan | |
| dc.contributor.author | Gurkan, Hakan | |
| dc.date.accessioned | 2026-02-08T15:15:41Z | |
| dc.date.available | 2026-02-08T15:15:41Z | |
| dc.date.issued | 2024 | |
| dc.department | Bursa Teknik Üniversitesi | |
| dc.description | 32nd IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2024 -- Tarsus Univ Campus, Mersin, TURKEY | |
| dc.description.abstract | This study proposes a speech compression method based on one-dimensional convolutional autoencoder and residual vector quantization. The proposed method offers different compression ratios at low bit rates. Speech quality evaluation metric (PESQ) was used to test the performance of the proposed method. Experimental results show that the proposed method achieves a PESQ value of 1.903 for 2.5 kbps and 2.24 for 5 kbps. | |
| dc.description.sponsorship | IEEE,IEEE Turkey,Koluman & Berdan,Loodos,Figes,Turkcell,Yildirim Elect | |
| dc.identifier.doi | 10.1109/SIU61531.2024.10600779 | |
| dc.identifier.isbn | 979-8-3503-8897-8 | |
| dc.identifier.isbn | 979-8-3503-8896-1 | |
| dc.identifier.issn | 2165-0608 | |
| dc.identifier.scopus | 2-s2.0-85200896483 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.uri | https://doi.org/10.1109/SIU61531.2024.10600779 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12885/5906 | |
| dc.identifier.wos | WOS:001297894700054 | |
| dc.identifier.wosquality | N/A | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | tr | |
| dc.publisher | Ieee | |
| dc.relation.ispartof | 32Nd Ieee Signal Processing and Communications Applications Conference, Siu 2024 | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | WOS_KA_20260207 | |
| dc.subject | Speech compression | |
| dc.subject | residual vector quantization | |
| dc.subject | convolutional autoencoder | |
| dc.subject | deep learning | |
| dc.title | Stacked causal convolutional autoencoder based speech compression method | |
| dc.title.alternative | Yığılmış nedensel evrişimsel otokodlayıcı tabanlı konuşma sıkıştırma yöntemi | |
| dc.type | Conference Object |












