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Multi-criteria subjective and objective evaluation 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''; PHC Procope 20142UD
    • بيانات النشر:
      HAL CCSD
    • الموضوع:
      2010
    • Collection:
      École Centrale Paris: HAL-ECP
    • الموضوع:
    • نبذة مختصرة :
      International audience ; In this paper, we address the problem of assessing the perceived quality of estimated source signals in the context of audio source separation. These signals involve different kinds of distortions depending on the considered separation algorithm, including distortion of the target source, interference from other sources or musical noise artifacts. A new MUSHRA-based subjective test protocol is proposed to assess the perceived quality with respect to each kind of distortion and collect the scores of 20 subjects over 80 sounds. Subsequently, the contribution of each type of distortion to the overall quality is analyzed. We propose a family of objective measures aiming to predict the subjective scores based on a decomposition of the estimation error into several distortion components. We conclude by discussing possible implications of this work in the field of 3D audio quality assessment.
    • Relation:
      inria-00545031; https://inria.hal.science/inria-00545031; https://inria.hal.science/inria-00545031/document; https://inria.hal.science/inria-00545031/file/2010-06-13_AES38_emiya.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.9B6B509C