%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{Imseng_ICASSP_2012,
         author = {Imseng, David and Bourlard, Herv{\'{e}} and Garner, Philip N.},
       projects = {Idiap, SNSF-MULTI, IM2},
          month = mar,
          title = {Using KL-divergence and multilingual information to improve ASR for under-resourced languages},
      booktitle = {Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing},
           year = {2012},
          pages = {4869--4872},
       location = {Kyoto},
       abstract = {Setting out from the point of view that automatic speech recognition (ASR) ought to benefit from data in languages other than the target language, we propose a novel Kullback-Leibler (KL) divergence based method that is able to exploit multilingual information in the form of universal phoneme posterior probabilities conditioned on the acoustics. We formulate a means to train a recognizer on  several different languages, and subsequently recognize speech in a target language for which only a small amount of data is available. Taking the Greek SpeechDat(II) data as an example, we show that the proposed formulation is sound, and show that it is able to outperform a current state-of-the-art HMM/GMM system. We also use a hybrid Tandem-like system to further understand the source of the benefit.},
            pdf = {https://publications.idiap.ch/attachments/papers/2012/Imseng_ICASSP_2012.pdf}
}