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Please use this identifier to cite or link to this item: https://elib.bsu.by/handle/123456789/306213
Title: Improving Spatial Resolution of First-order Ambisonics Using Sparse MDCT Representation
Authors: Likhachov, Denis
Petrovsky, Nick
Azarov, Elias
Keywords: ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика
ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика
Issue Date: 2023
Publisher: Minsk : BSU
Citation: Pattern Recognition and Information Processing (PRIP’2023). Artificial Universe: New Horisont : Proceedings of the 16 th International Conference, Belarus, Minsk, October 17–19, 2023 / Belarusian State University : eds. A. Nedzved, A. Belotserkovsky. – Minsk : BSU, 2023. – Pp. 122-125.
Abstract: The paper presents a method for improving spatial resolution of first-order ambisonic audio. The method is based on time/frequency decomposition of the audio with subsequent extraction of a directed plane wave from each frequency component. The method develops the basic ideas of high angular resolution planewave expansion (HARPEX) and directional audio coding (DirAC) taking advantage of real-valued sparse decomposition. Real-valued frequency components as opposed to complex-valued introduce simpler and more stable direction of arrival estimates, while sparse decomposition introduces an accurate and unified approach to describing sounds of different nature from transient to tonal sounds
URI: https://elib.bsu.by/handle/123456789/306213
ISBN: 978-985-881-522-6
Licence: info:eu-repo/semantics/openAccess
Appears in Collections:2023. Pattern Recognition and Information Processing (PRIP’2023). Artificial Intelliverse: Expanding Horizons

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