Active Learning for Sound Event Classification by Clustering Unlabeled Data

    Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

    31 Sitaatiot (Scopus)
    83 Lataukset (Pure)

    Abstrakti

    This paper proposes a novel active learning method to save annotation effort when preparing material to train sound event classifiers. K-medoids clustering is performed on unlabeled sound segments, and medoids of clusters are presented to annotators for labeling. The annotated label for a medoid is used to derive predicted labels for other cluster members. The obtained labels are used to build a classifier using supervised training. The accuracy of the resulted classifier is used to evaluate the performance of the proposed method. The evaluation made on a public environmental sound dataset shows that the proposed method outperforms reference methods (random sampling, certainty-based active learning and semi-supervised learning) with all simulated labeling budgets, the number of available labeling responses. Through all the experiments, the proposed method saves 50%–60% labeling budget to achieve the same accuracy, with respect to the best reference method.
    AlkuperäiskieliEnglanti
    Otsikko2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    KustantajaIEEE
    Sivut751-755
    ISBN (elektroninen)978-1-5090-4117-6
    DOI - pysyväislinkit
    TilaJulkaistu - 2017
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
    TapahtumaIEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING -
    Kesto: 1 tammik. 19001 tammik. 2000

    Julkaisusarja

    Nimi
    ISSN (elektroninen)2379-190X

    Conference

    ConferenceIEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING
    Ajanjakso1/01/001/01/00

    Julkaisufoorumi-taso

    • Jufo-taso 1

    Sormenjälki

    Sukella tutkimusaiheisiin 'Active Learning for Sound Event Classification by Clustering Unlabeled Data'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

    Siteeraa tätä