Abstract
Classical objective criteria evaluate speech quality using one quantity which embed all possible kinds of degradation. For speech denoising applications, there is a great need to determine with accuracy the kind of the degradation (residual background noise, speech distortion or both). In this work, we propose two perceptual bounds UBPE and LBPE defining regions where original and denoised signals are perceptually equivalent or different. Next, two quantitative criteria PSANR and PSADR are developed to quantify separately the two kinds of degradation. Some simulation results for speech denoising using different approaches show the usefulness of proposed criteria.
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Ben Aicha, A., Ben Jebara, S. (2007). Quantitative Perceptual Separation of Two Kinds of Degradation in Speech Denoising Applications. In: Chetouani, M., Hussain, A., Gas, B., Milgram, M., Zarader, JL. (eds) Advances in Nonlinear Speech Processing. NOLISP 2007. Lecture Notes in Computer Science(), vol 4885. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77347-4_20
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DOI: https://doi.org/10.1007/978-3-540-77347-4_20
Publisher Name: Springer, Berlin, Heidelberg
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