Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | AES Europe Spring 2022 - 152nd Audio Engineering Society Convention 2022 |
| Herausgeber (Verlag) | Audio Engineering Society |
| Seiten | 266-274 |
| Seitenumfang | 9 |
| ISBN (elektronisch) | 9781713855415 |
| Publikationsstatus | Veröffentlicht - 2022 |
| Veranstaltung | AES Europe Spring 2022 - 152nd Audio Engineering Society Convention 2022 - The Hague, Virtual, Niederlande Dauer: 16 Mai 2022 → 19 Mai 2022 |
Publikationsreihe
| Name | AES Europe Spring 2022 - 152nd Audio Engineering Society Convention 2022 |
|---|
Abstract
Near-field Head-Related Transfer Functions (HRTFs) depend on both source direction (azimuth/elevation) and distance. The acquisition procedure for near-field HRTF data on a dense spatial grid is time-consuming and prone to measurement errors. Therefore, existing databases only cover a few discrete source distances. Coming from the fact that continuous-azimuth acquisition of HRTFs has been made possible by applying the Normalized Least Mean Square (NLMS) adaptive filtering method, in this work we applied the NLMS algorithm in measuring near-field HRTFs under continuous variation of source distance. We developed and validated a novel measurement setup that allows the acquisition of near-field HRTFs for source distances ranging from 20 to 120 cm with one recording. We then evaluated the measurement accuracy by analyzing the estimation error from the adaptive filtering algorithm and the key characteristics of the measured HRTFs associated with near-field binaural rendering.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Mathematik (insg.)
- Modellierung und Simulation
- Physik und Astronomie (insg.)
- Akustik und Ultraschall
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AES Europe Spring 2022 - 152nd Audio Engineering Society Convention 2022. Audio Engineering Society, 2022. S. 266-274 (AES Europe Spring 2022 - 152nd Audio Engineering Society Convention 2022).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Acquisition of Continuous-Distance Near-Field Head-Related Transfer Functions on KEMAR Using Adaptive Filtering
AU - Li, Yuqing
AU - Preihs, Stephan
AU - Peissig, Jürgen
PY - 2022
Y1 - 2022
N2 - Near-field Head-Related Transfer Functions (HRTFs) depend on both source direction (azimuth/elevation) and distance. The acquisition procedure for near-field HRTF data on a dense spatial grid is time-consuming and prone to measurement errors. Therefore, existing databases only cover a few discrete source distances. Coming from the fact that continuous-azimuth acquisition of HRTFs has been made possible by applying the Normalized Least Mean Square (NLMS) adaptive filtering method, in this work we applied the NLMS algorithm in measuring near-field HRTFs under continuous variation of source distance. We developed and validated a novel measurement setup that allows the acquisition of near-field HRTFs for source distances ranging from 20 to 120 cm with one recording. We then evaluated the measurement accuracy by analyzing the estimation error from the adaptive filtering algorithm and the key characteristics of the measured HRTFs associated with near-field binaural rendering.
AB - Near-field Head-Related Transfer Functions (HRTFs) depend on both source direction (azimuth/elevation) and distance. The acquisition procedure for near-field HRTF data on a dense spatial grid is time-consuming and prone to measurement errors. Therefore, existing databases only cover a few discrete source distances. Coming from the fact that continuous-azimuth acquisition of HRTFs has been made possible by applying the Normalized Least Mean Square (NLMS) adaptive filtering method, in this work we applied the NLMS algorithm in measuring near-field HRTFs under continuous variation of source distance. We developed and validated a novel measurement setup that allows the acquisition of near-field HRTFs for source distances ranging from 20 to 120 cm with one recording. We then evaluated the measurement accuracy by analyzing the estimation error from the adaptive filtering algorithm and the key characteristics of the measured HRTFs associated with near-field binaural rendering.
UR - http://www.scopus.com/inward/record.url?scp=85136326868&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85136326868
T3 - AES Europe Spring 2022 - 152nd Audio Engineering Society Convention 2022
SP - 266
EP - 274
BT - AES Europe Spring 2022 - 152nd Audio Engineering Society Convention 2022
PB - Audio Engineering Society
T2 - AES Europe Spring 2022 - 152nd Audio Engineering Society Convention 2022
Y2 - 16 May 2022 through 19 May 2022
ER -