TU Berlin

Quality and Usability LabMarie-Neige Garcia

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Marie-Neige Garcia


Research Field:

- Quality and Usability

Research Topics:

- Video and Audio-Visual Quality Assessment
- Quality modeling



Since 2006: PhD Student at Technische Universität Berlin / Deutsche Telekom Laboratories

2004-2006: Project manager at ELDA (Evaluation and Language Resources Distribution Agency) , Speech evaluation department - Paris, France

  • Project manager in the EVALDA/EvaSy

    campaign (Evaluation of speech synthesis systems in French)

  • In charge of the evaluation of

    Text-to-speech systems in the European project TC-STAR (speech-to-speech


  • In charge of the evaluation of video

    technologies in the project CHIL (Pervasive Interaction Computing)

2003: Master’s Degree in Engineering at ISEP (Electronics Superior Institute of Paris); areas of study: informatics, telecommunications, electronics



Quality and Usability Lab
Deutsche Telekom Laboratories
TU Berlin
Ernst-Reuter-Platz 7
D-10587 Berlin, Germany




T-V-Model: Parameter-based Prediction of IPTV Quality
Citation key raake2008c
Author Raake, Alexander and Garcia, Marie-Neige and Möller, Sebastian and Berger, Jens and Kling, Frederik and List, Peter and Johann, Jens and Heidemann, Cornelius
Title of Book Proceedings of the IEEE Internation Conference on Acoustics, Speech and Signal Processing (ICASSP 20O8)
Pages 1149–1152
Year 2008
ISBN 978-1-4244-1483-3
Address Las Vegas, NV, United States
Month mar
Publisher IEEE
Abstract The paper presents a parameter-based model for predicting the perceived quality of transmitted video for IPTV applications. The core model we derived can be applied both to service monitoring and network or service planning. In its current form, the model covers H.264 and MPEG-2 coded video (standard and high definition) transmitted over IP-links. The model includes factors like the coding bit-rate, the packet loss percentage and the type of packet loss handling used by the codec. The paper provides an overview of the model, of its integration into a multimedia model predicting audio-visual quality, and of its application to service monitoring. A performance analysis is presented showing a high correlation with the results of different subjective video quality perception tests. An outlook highlights future model extensions
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