%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{Liang_ICASSP_2010,
         author = {Liang, Hui and Dines, John and Saheer, Lakshmi},
       keywords = {decision tree marginalization, HMM state mapping, unsupervised cross-lingual speaker adaptation},
       projects = {Idiap, EMIME},
          month = {3},
          title = {A Comparison of Supervised and Unsupervised Cross-Lingual Speaker Adaptation Approaches for HMM-Based Speech Synthesis},
      booktitle = {Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing},
           year = {2010},
       location = {Dallas, U.S.A.},
       crossref = {Liang_Idiap-RR-05-2010},
       abstract = {The EMIME project aims to build a personalized speech-to-speech translator, such that spoken input of a user in one language is used to produce spoken output that still sounds like the user's voice however in another language. This distinctiveness makes unsupervised cross-lingual speaker adaptation one key to the project's success. So far, research has been conducted into unsupervised and cross-lingual cases separately by means of decision tree marginalization and HMM state mapping respectively. In this paper we combine the two techniques to perform unsupervised cross-lingual speaker adaptation. The performance of eight speaker adaptation systems (supervised vs. unsupervised, intra-lingual vs. cross-lingual) are compared using objective and subjective evaluations. Experimental results show the performance of unsupervised cross-lingual speaker adaptation is comparable to that of the supervised case in terms of spectrum adaptation in the EMIME scenario, even though automatically obtained transcriptions have a very high phoneme error rate.},
            pdf = {https://publications.idiap.ch/attachments/papers/2009/Liang_ICASSP_2010.pdf}
}



crossreferenced publications: 
@TECHREPORT{Liang_Idiap-RR-05-2010,
         author = {Liang, Hui and Dines, John and Saheer, Lakshmi},
       projects = {Idiap, EMIME},
          month = {2},
          title = {A Comparison of Supervised and Unsupervised Cross-Lingual Speaker Adaptation Approaches for HMM-Based Speech Synthesis},
           type = {Idiap-RR},
         number = {Idiap-RR-05-2010},
           year = {2010},
    institution = {Idiap},
       crossref = {Liang_ICASSP_2010},
       abstract = {The EMIME project aims to build a personalized speech-to-speech translator, such that spoken input of a user in one language is used to produce spoken output that still sounds like the user's voice however in another language. This distinctiveness makes unsupervised cross-lingual speaker adaptation one key to the project's success. So far, research has been conducted into unsupervised and cross-lingual cases separately by means of decision tree marginalization and HMM state mapping respectively. In this paper we combine the two techniques to perform unsupervised cross-lingual speaker adaptation. The performance of eight speaker adaptation systems (supervised vs. unsupervised, intra-lingual vs. cross-lingual) are compared using objective and subjective evaluations. Experimental results show the performance of unsupervised cross-lingual speaker adaptation is comparable to that of the supervised case in terms of spectrum adaptation in the EMIME scenario, even though automatically obtained transcriptions have a very high phoneme error rate.},
            pdf = {https://publications.idiap.ch/attachments/reports/2010/Liang_Idiap-RR-05-2010.pdf}
}