TU Berlin

Quality and Usability LabBenjamin Belmudez

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Benjamin Belmudez


Research Field

Audiovisual quality

Research Topics

Multimodal Quality Assessment on Videoconferencing


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


Contributions to Teaching

  • Exercises “Usability Engineering”, Technical University Berlin, 2008-2009


Call Quality Prediction for Audiovisual Time-Varying Impairments Using Simulated Conversational Structures
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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