Inhalt des Dokuments
Benjamin Belmudez
[1]- © Copyright??
Research Field
Audiovisual quality
Research Topics
Multimodal Quality Assessment on Videoconferencing
Biography
Benjamin was born in France in
1983. He first studied general Mathematics and Physics in Toulouse.
Then he joined the National School of Higher Education in Physics of
Strasbourg (Engineering school) and specialized in Video and Image
Processing. He carried out his master's degree within the INRIA in
cooperation with the LIAMA (Beijing) on "Structural Change
Detectection on Satellite Images using Conditional Mixed States
Markovian Model". In 2007, he started a Phd within the Deutsche
Telekom Laboratories and the Technical University of Berlin.
Address Quality and Usability Lab
Deutsche Telekom Laboratories
TU Berlin
Ernst-Reuter-Platz
7
D-10587 Berlin, Germany Tel: +49 30 8353 58233
Publications
| Zitatschlüssel | belmudez2013a |
|---|---|
| Autor | Belmudez, Benjamin and Lewcio, Blazej and Möller, Sebastian |
| Seiten | 792–805 |
| Jahr | 2013 |
| ISSN | 1610-1928 |
| DOI | 10.3813/AAA.918657 |
| Adresse | Stuttgart, Germany |
| Journal | Acta Acustica united with Acustica |
| Jahrgang | 99 |
| Nummer | 5 |
| Monat | sep |
| Verlag | Hirzel, Stuttgart |
| Wie herausgegeben | full |
| Zusammenfassung | In this study we present an evaluation and improvement of time integration speech quality models applied to assess fluctuating quality of audiovisual transmission. We first introduce a subjective test methodology to evaluate the user perception of time-varying quality of 90 seconds long sequences that are organized in a simulated conversational structure. We conducted a two-fold user test where in the first part, the quality of simulated video-telephony conversations was assessed. Audiovisual impairments were temporally distributed to follow predefined quality profiles. In the second part of the experiment, subjective ratings of short audiovisual samples (9 seconds) constituent of the simulated conversations are gathered. The results of both experiments show that the end-dialog judgments are closely correlated to the plain average of the short samples. The modeling results for call quality models that predict the quality at the end of a (simulated) conversation are described. These models proved to enhance the prediction accuracy in comparison to the plain average, and an optimization of the models' parameters further refines the correlation of the estimates with the subjective data. The optimized models also showed a higher correlation and a lower prediction error on independent test data. |
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