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Beat Tracking: Is 44.1 kHz Really Needed?

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU148273" target="_blank" >RIV/00216305:26220/23:PU148273 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.13164/eeict.2023.227" target="_blank" >10.13164/eeict.2023.227</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Beat Tracking: Is 44.1 kHz Really Needed?

  • Original language description

    Beat tracking is essential in music information retrieval, with applications ranging from music analysis and automatic playlist generation to beat-synchronized effects. In recent years, deep learning methods, usually inspired by well-known architectures, outperformed other beat tracking algorithms. The current state-of-the-art offline beat tracking systems utilize temporal convolutional and recurrent networks. Most systems use an input sampling rate of 44.1 kHz. In this paper, we retrain multiple versions of state-of-the-art temporal convolutional networks with different input sampling rates while keeping the time resolution by changing the frame size parameter. Furthermore, we evaluate all models using standard metrics. As the main contribution, we show that decreasing the input audio recording sampling frequency up to 5 kHz preserves most of the accuracy, and in some cases, even slightly outperforms the standard approach.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings II of the 29th Conference STUDENT EEICT 2023 Selected Papers

  • ISBN

    978-80-214-6154-3

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    227-231

  • Publisher name

    Brno University of Technology, Faculty of Elektronic Engineering and Communication

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Apr 25, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article