Abstract
This paper proposed an improved objective audio quality estimation system compatible with PEAQ (Perceptual Evaluation of Audio Quality). Based on the computational auditory model, we used a novel psychoacoustic model to assess the quality of highly impaired audio. We also applied the robust linear MOA (Least-squares Weight Vector algorithm) and MinmaxMOA (Minmax-Optimized MOV Selection algorithm) to cognitive model of the estimation system. Compared to the PEAQ advanced version, the proposed estimation system has a considerable improvement in performance both in terms of the correlation and MSE (Mean Square Error). By combining the computational auditory model and PEAQ, our estimation system can be applied to the quality assessment of highly impaired audio.
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References
Dau, T., Kollmeier, B., Kohlrausch, A.: A quantitative model of the effective signal processing in the auditory system. I. Model structure. The Journal of the Acoustical Society of America 99, 3615–3622 (1996)
Hansen, M., Kollmeier, B.: Using a quantitative psychoacoustical signal representation for objective speech quality measurement. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1997, vol. 2, pp. 1387–1390 (1997)
ITU-R recommendation BS.1387-1. Methods for Objective Measurements of Perceived Audio Quality. ITU-R Recommendation BS.1387-1 (2001)
Campbell, D., Jones, E., Glavin, M.: Audio quality assessment techniques-A review, and recent developments. Signal Process 89, 1489–1500 (2009)
Creusere, C.D.: Understanding perceptual distortion in MPEG scalable audio coding. IEEE Transactions on Speech and Audio Processing 13, 422–431 (2005)
Huber, R., Kollmeier, B.: PEMO-Q:A New Method for Objective Audio Quality Assessment Using a Model of Auditory Perception. IEEE Transactions on Audio, Speech, and Language Processing 14, 1902–1911 (2006)
Dau, T., Kollmeier, B., Kohlrausch, A.: Modeling auditory processing of amplitude modulation. I. Detection and masking with narrow-band carriers. The Journal of the Acoustical Society of America 102, 2892–2905 (1997)
Guo, Z.: Objective Audio Quality Assessment Based on Spectro-Temporal Modulation Analysis. Master’s Degree Project of Stockholm, Sweden (2011)
Morten, L.J., Stephan, D.E., Torsten, D.: A computational model of human auditory signal processing and perception. The Journal of the Acoustical Society of America 124, 422–438 (2008)
Creusere, C.D., Kallakuri, K.D., Vanam, R.: An Objective Metric of Human Subjective Audio Quality Optimized for a Wide Range of Audio Fidelities. IEEE Transactions on Audio, Speech, and Language Processing 16, 129–136 (2008)
Zhu, M.Y.: Zheng. J., Yu, X.Q., Wan, W.G.: Audio Quality Assessment Improvement via Circular and Flexible Overlap. In: 2011 IEEE International Symposium on Multimedia (ISM), pp. 47–52 (2011)
Zhu, M.Y., Zheng, J., Yu, X.Q., Wan, W.G.: Streaming audio packet loss concealment based on sinusoidal frequency estimation in MDCT domain. IEEE Transactions on Consumer Electronics 56, 811–819 (2010)
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Zheng, J., Zhu, M., He, J., Yu, X. (2012). PEAQ Compatible Audio Quality Estimation Using Computational Auditory Model. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34478-7_11
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DOI: https://doi.org/10.1007/978-3-642-34478-7_11
Publisher Name: Springer, Berlin, Heidelberg
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