%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{Madikeri_ICASSP2019_2019,
         author = {Madikeri, Srikanth and Dey, Subhadeep and Motlicek, Petr},
       keywords = {bayesian fusion, inter-task fusion, speaker recognition},
       projects = {SIIP},
          month = may,
          title = {A BAYESIAN APPROACH TO INTER-TASK FUSION FOR SPEAKER RECOGNITION},
      booktitle = {In Proceedings of ICASSP 2019},
           year = {2019},
          pages = {5786-5790},
       location = {Brighton, ENGLAND},
           issn = {1520-6149},
           isbn = {978-1-4799-8131-1},
       crossref = {Madikeri_Idiap-RR-07-2020},
       abstract = {In i-vector based speaker recognition systems, back-end classifiers are trained to factor out nuisance information and retain only the speaker identity. As a result, variabilities arising due to gender, language and accent ( among many others) are suppressed. Inter-task fusion, in which such metadata information obtained from automatic systems is used, has been shown to improve speaker recognition performance. In this paper, we explore a Bayesian approach towards inter-task fusion. Speaker similarity score for a test recording is obtained by marginalizing the posterior probability of a speaker. Gender and language probabilities for the test audio are combined with speaker posteriors to obtain a final speaker score. The proposed approach is demonstrated for speaker verification and speaker identification tasks on the NIST SRE 2008 dataset. Relative improvements of up to 10\% and 8\% are obtained when fusing gender and language information, respectively.},
            pdf = {https://publications.idiap.ch/attachments/papers/2019/Madikeri_ICASSP2019_2019.pdf}
}



crossreferenced publications: 
@TECHREPORT{Madikeri_Idiap-RR-07-2020,
         author = {Madikeri, Srikanth and Dey, Subhadeep and Motlicek, Petr},
       projects = {SIIP},
          month = {3},
          title = {A BAYESIAN APPROACH TO INTER-TASK FUSION FOR SPEAKER RECOGNITION},
           type = {Idiap-RR},
         number = {Idiap-RR-07-2020},
           year = {2020},
    institution = {Idiap},
            pdf = {https://publications.idiap.ch/attachments/reports/2018/Madikeri_Idiap-RR-07-2020.pdf}
}