Bekiryazici, TahirAydemir, GurkanGurkan, Hakan2026-02-082026-02-082024979-8-3503-8897-8979-8-3503-8896-12165-0608https://doi.org/10.1109/SIU61531.2024.10600779https://hdl.handle.net/20.500.12885/590632nd IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2024 -- Tarsus Univ Campus, Mersin, TURKEYThis 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.trinfo:eu-repo/semantics/closedAccessSpeech compressionresidual vector quantizationconvolutional autoencoderdeep learningConference Object10.1109/SIU61531.2024.10600779WOS:0012978947000542-s2.0-85200896483N/AN/A