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Multimedia Systems
Erschienen in: Multimedia Systems 5/2016

01.10.2016 | Regular Paper

VoIP quality measurement: subjective VoIP quality estimation model for G.711 and G.729 based on native Thai users

verfasst von: Therdpong Daengsi, Nalakkhana Khitmoh, Pongpisit Wuttidittachotti

Erschienen in: Multimedia Systems | Ausgabe 5/2016

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Abstract

This paper presents a mathematical model that has been created from the subjective MOS, instead of modifying or improving the existing objective measurement methods (e.g., E-model) for VoIP quality measurement. The proposed model of VoIP quality measurement method is based on native Thai users who communicate to each other using Thai language, which is a tonal language, unlike English and most western languages. The data have been gathered using conversation-opinion tests with 400 and 354 native Thai subjects for two popular codecs, G.711 and G.729, respectively, referring to effects from two major network factors, packet loss and packet delay. This model is called the Thai subjective VoIP quality evaluation model (ThaiVQE). It has been evaluated using two test sets of subjective MOS, from 50 native Thai subjects for G.711 and 64 native Thai subjects for G.729, then the results have been compared with the E-model results. Based on native Thai users, the evaluation result surprisingly shows that ThaiVQE can contribute better accuracy and reliability than the standard E-model with error reduction of over 13 % for G.711 and 28 % for G.729. Therefore, this is an example study for other countries that have their own languages and cultures to create their subjective MOS model.
Vorheriger Artikel Optimal tree packing for discretized live rate-adaptive streaming in CDN
Nächster Artikel RecAm: a collaborative context-aware framework for multimedia recommendations in an ambient intelligence environment

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Literatur
1.
2.
3.
4.
Yang, Q., Pitts, J.M.: Scalable voice over Internet protocol service-level agreement guarantees in converged transmission control protocol/Internet protocol networks. IET Commun. 4(8), 1026–1035 (2010)MathSciNetCrossRefMATH
5.
6.
7.
Cai, Z., Kitawaki, N., Yamada, T., Makino, S.: Comparison of MOS evaluation characteristics for Chinese, Japanese and English in IP telephony. In: Proceedings of IUCS 2010, Beijing, pp. 1–4 (2010)
8.
Takahashi, A., Kurashima, A., Yoshino, H.: Objective assessment methodology for estimating conversational quality in VoIP. IEEE Audio Speech Lang Process. 14(6), 1983–1993 (2006)
9.
Ren, J., Zhang, C., Huang, W., Mao, D.: Enhancement to E-model on standard deviation of packet delay. In: Proceedings of ICIS 2010, Chengdu, pp. 256–259 (2010)
10.
Daengsi, T., Wutiwiwatchai, C., Preechayasomboon, A., Sukparungsee, S.: A study of VoIP quality evaluation: user perception of voice quality from G.729, G.711 and G.722. In: Proceedings of IEEE CCNC—SS-QoE, Lasvegas, pp. 342–345 (2012)
11.
Wutiwiwatchai, C., Furui, S.: Thai speech processing technology: a review. Speech Commun. 49, 8–27 (2007)CrossRef
12.
Gandour, J., Wong, D., Hsieh, L., Weinzapfel, B., Lancker, D.V., Hutchins, G.D.: A crosslinguistic PET study of tone perception. J. Cogn. Neurosci. 12(1), 207–222 (2000)CrossRef
13.
Sittiprapaporn, W., Chindaduangratn, C., Kotchabhakdi, N.: Long-term memory traces for familiar spoken words in tonal languages as revealed by the Mismatch negativity. Songklanakarin J. Sci. Technol. 26(6), 779–786 (2004)
14.
15.
Sathapornvajana, S., Papasratorn, B.: Effect of culture, age, and language on quality of services and adoption of IP applications. Wirel. Pers. Commun. 69, 1067–1075 (2013)CrossRef
16.
Khan, A., Sun, L., Jammeh, E., Ifeachor, E.: Quality of experience-driven adaptation scheme for video applications over wireless networks. IET Commun. 4(11), 1337–1347 (2010)CrossRef
17.
ITU-T.: ITU-T Recommendation P.10/G.100 Vocabulary for performance and quality of service, Amendment 1—New Appendix I—Definition of Quality of Experience (QoE) (2007)
18.
Scharts, R., Hoßfeld, T., Janowski, L., Egger, S.: From Packets to People: Quality of Experience as a New Measurement Challenge. Data Traffic Monitoring and Analysis (Book Section), Lecture Notes in Computer Science 7754, pp. 219–263 (2013)
19.
Batteram, H., Damm, G., Mukhopadhyay, A., Philippart, L., Odysseos, R., Urrutia-Valdés, C.: Delivering quality of experience in multimedia networks. Bell Labs Tech. J. 15(1), 175–194 (2010)CrossRef
20.
21.
Lindeberg, M., Kristiansen, S., Plagemann, T., Goebel, V.: Challenges and techniques for video streaming over mobile ad hoc networks. Multimed. Syst. 17, 51–82 (2011)CrossRef
22.
23.
Ding, L., Lin, Z., Radwan, A., El-Hennaway, M., Goubran, R.: Non-intrusive single-ended speech quality assessment in VoIP. Speech Commun. 49, 477–489 (2007)CrossRef
24.
Goudarzi M (2008) Evaluation of Voice Quality in 3G Mobile Networks. Thesis, University of Plymouth
25.
Al-Akhras, M., Zedan, H., John, R., Almomani, I.: Non-intrusive speech quality prediction in VoIP networks using a neural network approach. Neurocomputing 72, 2595–2608 (2009)CrossRef
26.
Mahdi, A.E., Picovici, D.: Advances in voice quality measurement in modern telecommunications. Dig. Signal Process. 19, 79–103 (2009)CrossRef
27.
ITU-T.: ITU-T Recommendation P.800 Methods for subjective determination of transmission quality (1996)
28.
ITU-T.: ITU-T Recommendation P.805 Subjective evaluation of conversational quality (2007)
29.
Dymarski, P., Kula, S., Huy, T.N.: QoS conditions for VoIP and VoD. J. Telecommun. Inf. Technol. 3, 29–37 (2011)
30.
Daengsi, T., Sukparungsee, S., Wutiwiwatchai, C., Preechayasomboon, A.: Comparison of perceptual voice quality of VoIP provided by G.711 and G.729 using conversation-opinion tests. Int. J. Comput. Internet Manag. 20(1), 2012–2026 (2012)
31.
32.
ITU-T.: ITU-T Recommendation G.107 The E-model: a computational model for use in transmission planning (2011)
33.
ITU-T.: ITU-T Recommendation P.800.1 Mean Opinion Score (MOS) terminology (1996)
34.
ITU-T.: ITU-T Recommendation G.107 The E-model: a computational model for use in transmission planning (2009)
35.
Voznak, M.: Non-intrusive speech quality assessment in simplified E-Model. WSEAS Trans. Syst. 11(8), 315–325 (2012)
36.
Voznak, M.: E-model modification for case of cascade codecs arrangement. Int. J. Math. Model Met. Appl. Sci. 6(8), 1301–1309 (2011)
37.
Zhang, H., Xie, L., Byun, J., Flynn, P., Shim, C.: Packet loss burstiness and enhancement to the E-model. In: Proceedings of SNPD/SAWN 2005, Towson, pp. 214–219 (2005)
38.
Zheng, H., Lin, Q.: Non-intrusive speech quality assessment in VoIP using the extended E-model. Energy Proc. 13, 6867–6874 (2011)CrossRef
39.
Ding, L., Goubran, R.A.: Speech quality prediction in VoIP using the extended E-model. In: Proceedings of IEEE GLOBECOM 2003, San Francisco, vol. 7, pp. 3974–3978 (2003)
40.
Assem, H., Malone, D., Dunne, J., O’Sullivan, P.: Monitoring VoIP call quality using improved simplified E-model. In: Proceedings of ICNC 2013, San Diego, pp. 927–931 (2013)
41.
ITU-T.: ITU-T Recommendation G.711, pulse code modulation (PCM) of voice frequencies (1988)
42.
ITU-T.: ITU-T Recommendation G.729, coding of speech at 8 kb/s using conjugate-structure algebraic-code-excited linear prediction (CS-ACELP) (2012)
43.
Daengsi, T., Yochanang, K., Wuttiditachotti, P.: A study of perceptual VoIP quality evaluation with Thai users and codec selection using voice quality: bandwidth tradeoff analysis. In: Proceedings of ICTC 2013, Jeju, pp. 691–696 (2013)
44.
Karapantazis, S., Pavlidou, F.-N.: VoIP: A comprehensive survey on a promising technology. Comput. Netw. 53(12), 2050–2090 (2009)CrossRef
45.
ITU-T.: ITU-T Recommendation P.862.3 application guide for objective quality measurement based on recommendations P.862, P.862.1 and P.862.2 (2007)
46.
47.
48.
49.
50.
51.
52.
ITU-T.: ITU-T Recommendation G.114. One-way transmission time (2003)
53.
54.
Markopoulou, A., Iannaccone, G., Bhattacharyya, S., Chuah, C.-N., Diot, C.: Characterization of failures in an IP backbone. In: Proceedings of IEEE INFOCOM 2004, Hong Kong, pp. 2307–2317 (2004)
55.
Sun, L., Ifeachor, E.C., Perceived speech quality prediction for voice over IP-based networks. In: Proceedings of IEEE ICC 2002, New York, vol. 4, pp. 2573–2577 (2002)
56.
57.
Ren, J., Zhang, H., Zhu, Y., Gao, C. Assessment of effects of different language in VOIP. In: Proceedings of ICALIP 2008, Shanghai, pp. 1624–1628 (2008)
58.
Daengsi, T., Wuttidittachotti, P. VoIP quality measurement: enhanced E-model using bias factor. In: Proceedings of IEEE Globecom 2013, Atlanta, pp. 1351–1356 (2013)
59.
Rahdari, F., Eftekhari, M., Akbari, A., Zeinalkhani, M.: Developing fuzzy models for estimating the quality of VoIP. Iran. J. Fuzzy Syst. 11(1), 49–73 (2013)MathSciNet
60.
Calyam, P., Ekici, E., Lee, C.-G., Haffner, M., Howes, N.: A “GAP-model” based framework for online VVoIP QoE measurement. J. Commun. Netw. 9(4), 446–456 (2007)CrossRef
61.
Sun, L. Speech quality prediction for voice over internet protocol networks. Dissertation, University of Plymouth (2004)
62.
Yaodu, W., Xiang, X., Jingming, K., Chillon, M.G.: Subjective speech quality evaluation based on collecting opinions via internet. In: Proceedings of international conference communications and mobile computing 2010, Shenzhen, pp. 517–521 (2010)
63.
Daengsi, T., Wuttidittachotti, P., Preechayasomboon, A., Wutiwiwatchai, C., Sukparungsee, S.: VoIP quality of experience: a proposed subjective MOS estimation model based-on Thai users. In: Proceedings of ICUFN 2013, Da Nang, pp. 407–412 (2013)
64.
Khitmah, N., Daengsi, T., Wuttidittachotti, P.: A subjective—VoIP quality estimation model for G.729 based on native Thai users. In: Proceedings of ICACT 2014, Pyeongchang, pp. 48–53 (2014)
65.
Sun, L., Ifeachor, E.C.: Voice quality prediction models and their application in VoIP networks. IEEE Trans. Multimed. 8(4), 809–820 (2006)CrossRef
66.
Simionovici, A.-M., Tantar, A.-A., Bouvry, P., Didelot, L.: Predictive modeling in a VoIP system. J. Telecommun. Inf. Technol. 4, 32–40 (2013)
67.
Babinec, S., Pospchal, J.: Modular echo state neural networks in time series prediction. Comput. Inf. 30(2), 321–334 (2011)
68.
Chen, R.J.C., Bloomfield, P., Cubbage, F.W.: Comparing forecasting models in tourism. J. Hosp. Tour. Res. 32, 3–21 (2008)CrossRef
69.
Johannesson, N.O.: The ETSI computation model: a tool for transmission planning of telephone networks. IEEE Commun. Mag. 35, 70–79 (1997)CrossRef
Metadaten
Titel
VoIP quality measurement: subjective VoIP quality estimation model for G.711 and G.729 based on native Thai users
verfasst von
Therdpong Daengsi
Nalakkhana Khitmoh
Pongpisit Wuttidittachotti
Publikationsdatum
01.10.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Multimedia Systems / Ausgabe 5/2016
Print ISSN: 0942-4962
Elektronische ISSN: 1432-1882
DOI
https://doi.org/10.1007/s00530-015-0468-3

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