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@TECHREPORT{Pronobis_Idiap-RR-73-2008,
         author = {Pronobis, Marianna and Magimai.-Doss, Mathew},
       projects = {Idiap, AMIDA},
          month = {11},
          title = {Integrating audio and vision for robust automatic gender recognition},
           type = {Idiap-RR},
         number = {Idiap-RR-73-2008},
           year = {2008},
    institution = {Idiap},
       abstract = {We propose a multi-modal Automatic Gender Recognition (AGR) system based on audio-visual cues and present its thorough evaluation in realistic scenarios. First, we analyze robustness of different audio and visual features under varying conditions and create two uni-modal AGR systems. Then, we build an integrated audio-visual system by fusing information from each modality at the classifier level. Our extensive studies on the BANCA corpus comprising datasets of varying complexity show that: (a) the audio-based system is more robust than the vision-based system; (b) integration of audio-visual cues yields a resilient system and improves performance in noisy conditions.},
            pdf = {https://publications.idiap.ch/attachments/reports/2008/Pronobis_Idiap-RR-73-2008.pdf}
}