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Subjective and objective quality assessment of audio source separation

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  • معلومة اضافية
    • Contributors:
      Speech and sound data modeling and processing (METISS); Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA); Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes); Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes); Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique; Institut National de Recherche en Informatique et en Automatique (Inria); Medizinische Physik; Carl Von Ossietzky Universität Oldenburg = Carl von Ossietzky University of Oldenburg (OFFIS); French Ministry of Foreign and European Affairs, French Ministry of Higher Education and Research and German Academic Exchange Service under project Procope 20142UD; German Federal Ministry of Education and Research under project number 01EZ0741 ''Model-based hearing systems''; Procope 20142UD
    • بيانات النشر:
      HAL CCSD
      Institute of Electrical and Electronics Engineers
    • الموضوع:
      2011
    • Collection:
      École Centrale Paris: HAL-ECP
    • نبذة مختصرة :
      International audience ; We aim to assess the perceived quality of estimated source signals in the context of audio source separation. These signals may involve one or more kinds of distortions, including distortion of the target source, interference from the other sources or musical noise artifacts. We propose a subjective test protocol to assess the perceived quality with respect to each kind of distortion and collect the scores of 20 subjects over 80 sounds. We then propose a family of objective measures aiming to predict these subjective scores based on the decomposition of the estimation error into several distortion components and on the use of the PEMO-Q perceptual salience measure to provide multiple features that are then combined. These measures increase correlation with subjective scores up to 0.5 compared to nonlinear mapping of individual state-of-the-art source separation measures. Finally, we released the data and code presented in this paper in a freely-available toolkit called PEASS.
    • Relation:
      inria-00567152; https://inria.hal.science/inria-00567152; https://inria.hal.science/inria-00567152/document; https://inria.hal.science/inria-00567152/file/emiya2011.pdf
    • الرقم المعرف:
      10.1109/TASL.2011.2109381
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.5B71288B