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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jelassi, S. Rubino, G. |
| Copyright Year | 2011 |
| Description | Author affiliation: IRISA / INRIA Rennes, France (Jelassi, S.; Rubino, G.) |
| Abstract | The paper delves the behavior rating of new emerging automatic quality assessors of VoIP calls subject to bursty packet loss process. The examined speech quality assessment (SQA) algorithms are able to estimate speech quality of live VoIP calls at run-time using control information extracted from header content of received packets. They are especially designed to be sensitive to packet loss burstiness. The performance evaluation study is performed using a dedicated set-up software-based SQA framework. It offers a personalized packet killer and includes implementation of four SQA algorithms. A speech quality database, which covers a wide range of bursty packet loss conditions, has been created then thoroughly analyzed. Our important findings are the following: (1) all examined automatic bursty-loss aware speech quality assessors achieve a satisfactory correlation under upper (>20%) and lower (<10%) ranges of packet loss process (2) They exhibit a clear weakness to assess speech quality under a moderated packet loss process (3) The accuracy of sequence-by-sequence basis of examined SQA algorithms should be addressed in details for further precision. |
| Starting Page | 415 |
| Ending Page | 420 |
| File Size | 290275 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424487899 |
| e-ISBN | 9781424487905 |
| DOI | 10.1109/CCNC.2011.5766503 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-01-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Speech Algorithm design and analysis Loss measurement Correlation Speech coding Accuracy Genomics Bursty packet losses VoIP QoE Artificial speech quality assessors |
| Content Type | Text |
| Resource Type | Article |
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