Fast Low-Latency Convolution by Low-Rank Tensor Approximation

Martin Jälmby, Filip Elvander, Toon van Waterschoot

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

4 Lataukset (Pure)

Abstrakti

In this paper we consider fast time-domain convolution, exploiting low-rank properties of an impulse response (IR). This reduces the computational complexity, speeding up the convolution, without introducing latency. Previous work has considered a truncated singular value decomposition (SVD) of a two-dimensional matricization, or reshaping, of the IR. We here build upon this idea, by providing an algorithm for convolution with a three-dimensional tensorization of the IR. We provide simulations using real-life acoustic room impulse responses (RIRs) of various lengths, convolving them with music, as well as speech signals. The proposed algorithm is shown to outperform the comparable existing algorithm in terms of signal quality degradation, for all considered scenarios, without increasing the computational complexity, or the memory usage.
AlkuperäiskieliEnglanti
OtsikkoICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
KustantajaIEEE
Sivut1-5
Sivumäärä5
ISBN (elektroninen)978-1-7281-6327-7
ISBN (painettu)978-1-7281-6328-4
DOI - pysyväislinkit
TilaJulkaistu - 10 kesäk. 2023
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE International Conference on Acoustics, Speech, and Signal Processing - Rhodes Island, Kreikka
Kesto: 4 kesäk. 202310 kesäk. 2023

Julkaisusarja

Nimi Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
ISSN (elektroninen)2379-190X

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing
LyhennettäICASSP
Maa/AlueKreikka
KaupunkiRhodes Island
Ajanjakso04/06/202310/06/2023

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