Abstract
This paper proposes a new signal-aware parametric quality assessment model for audio and speech over IP. The perceptual importance of the reproducing packets and relevant neighborhoods are included in the model. The model is developed from a built audio and speech quality assessment framework using the Artificial Neural Networks(ANN). The overall quality is evaluated by combining the signal-aware parameters with network parameters using a large set of audio and speech samples. It is shown that the signal-aware approach gains higher correlation with the improved PEAQ outputs compared with other parametric method such as E-model.
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Xie, S. et al. (2015). Signal-Aware Parametric Quality Model forĀ Audio and Speech over IP Networks. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8935. Springer, Cham. https://doi.org/10.1007/978-3-319-14445-0_42
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DOI: https://doi.org/10.1007/978-3-319-14445-0_42
Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-14445-0
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