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Speech quality estimation of voice over internet protocol codec using a packet loss impairment model
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1.
1.ITU-T Recommendation, P. 862: Perceptual Evaluation of Speech Quality (PESQ): An Objective Method for End-to-End Speech Quality Assessment of Narrow-Band Telephone Networks and Speech Codecs (International Telecommunication Union, Geneva, Feb. 2001).
2.
2.ITU-T Recommendation, P. 563: Single-Ended Method for Objective Speech Quality Assessment in Narrow-Band Telephony Applications (International Telecommunication Union, Geneva, May 2004).
3.
3.ITU-T Recommendation, G. 107: The E-model: A Computational Model for Use in Transmission Planning (International Telecommunication Union, Geneva, Dec. 2011).
4.
4. A. W. Rix, J. G. Beerends, D.-S. Kim, P. Kroon, and O. Ghitza, “Objective assessment of speech and audio quality—Technology and applications,” IEEE Trans. Audio Speech Language Processing 14(6), 18901901 (2006).
http://dx.doi.org/10.1109/TASL.2006.883260
5.
5. L. Ding, Z. Lin, A. Radwan, M. S. El-hennawey, and R. A. Goubran, “Non-intrusive single-ended speech quality assessment in VoIP,” Speech Commun. 49(6), 477489 (2007).
http://dx.doi.org/10.1016/j.specom.2007.04.003
6.
6. M.-K. Lee, K.-T. Kim, H.-G. Kang, and D. H. Youn, “Speech quality estimation using packet loss effects in CELP-type speech coders,” Proc. Interspeech 2007, 16971700 (2007).
7.
7. S. Jelassi, H. Youssef, C. Hoene, and G. Pujolle, “Voicing-aware parametric speech quality models over VoIP networks,” in Proceedings of the Second International Conference on Global Information Infrastructure Symposium, GIIS'09 (June 2009), pp. 120127.
8.
8. K. Vos, S. Jensen, and K. Soerensen, “SILK Speech Codec,” Technical Report draft-vos-silk-02 (IETF Secretariat, Fremont, CA, 2010).
9.
9.ITU-T Recommendation, P. 862.2: Wideband Extension to Recommendation p. 862 for the Assessment of Wideband Telephone Networks and Speech Codecs (International Telecommunication Union, Geneva, Nov. 2007).
10.
10.ITU-T Recommendation, P. 800: Methods for Subjective Determination of Transmission Quality (International Telecommunication Union, Geneva, Aug. 1996).
11.
11.ITU-R Recommendation, B. S. 1534-1: Methods for Subjective Assessment of Intermediate Quality Levels of Coding Systems (International Telecommunication Union, Geneva, Jan. 2003).
12.
12.ITU-T Recommendation, P. Sup23: ITU-T Coded-Speech Database (International Telecommunication Union, Geneva, Feb. 1998).
13.
13. L. R. Rabiner and M. R. Sambur, “Application of an LPC distance measure to the voiced-unvoiced-silence detection problem,” IEEE Trans. Acoust. Speech Signal Processing 25(4), 338343 (1977).
http://dx.doi.org/10.1109/TASSP.1977.1162964
14.
14. M. Chibani, R. Lefebvre, and P. Gournay, “Fast recovery for a CELP-like speech codec after a frame erasure,” IEEE Trans. Audio Speech Language Processing 15(8), 24852495 (2007).
http://dx.doi.org/10.1109/TASL.2007.907332
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Figures

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FIG. 1.

The average and standard deviation of the P.862.2 degradation scores for the one, two and three consecutive frame error cases where the previous and following frame is given as silence (S), unvoiced (UV) and voiced (V) characteristic.

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FIG. 2.

(Color online) The average LP spectrum and spectral centroid for LTP inactive (left) and LTP active (right) frames.

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FIG. 3.

(Color online) MUSHRA test results.

Tables

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TABLE I.

Categorization of SILK frame.

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TABLE II.

The results of PLC impairment estimation.

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/content/asa/journal/jasa/134/5/10.1121/1.4824628
2013-10-16
2014-04-19

Abstract

This letter proposes a degradation and cognition model to estimate speech quality impairment because of packet loss concealment (PLC) algorithm implemented in the speech CODEC SILK. By considering the fact that the quality degradation caused by packet loss is highly related to the PLC algorithm, the impact of quality degradation on various types of previous and lost packet classes is analyzed. Then, the PLC effects to the proposed class types are measured by the class conditional expectation of the degradation scores. Finally, the cognition module is derived to estimate the total quality degradation in a mean opinion score (MOS) scale. When assessed for correlation with subject test results, the correlation coefficient of the encoder-based class model is 0.93, and that of the decoder-based model is 0.87.

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Scitation: Speech quality estimation of voice over internet protocol codec using a packet loss impairment model
http://aip.metastore.ingenta.com/content/asa/journal/jasa/134/5/10.1121/1.4824628
10.1121/1.4824628
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