%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{weber-ar-00-30,
         author = {Weber, Katrin and Bengio, Samy and Bourlard, Herv{\'{e}}},
       projects = {Idiap},
          month = {10},
          title = {{HMM2}- {A} {N}ovel {A}pproach to {HMM} Emission {P}robability Estimation},
      booktitle = {International Conference on Spoken Langugae Processing (ICSLP 2000)},
           year = {2000},
        address = {Beijing, China},
           note = {IDIAP-rr 00-30},
       crossref = {weber-rr-00-30},
       abstract = {In this paper, we discuss and investigate a new method to estimate local emission probabilities in the framework of hidden Markov models (HMM). Each feature vector is considered to be a sequence and is supposed to be modeled by yet another HMM. Therefore, we call this approach `HMM2'. There is a variety of possible topologies of such HMM2 systems, e.g. incorporating trellis or ergodic HMM structures. Preliminary HMM2 speech recognition experiments on cepstral and spectral features yielded worse results than state-of-the-art systems. However, we believe that HMM2 systems have a lot of potential advantages and are therefore worth investigating further.},
            pdf = {https://publications.idiap.ch/attachments/reports/2000/rr00-30.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2000/rr00-30.ps.gz},
ipdmembership={speech},
language={English},
}



crossreferenced publications: 
@TECHREPORT{weber-rr-00-30,
         author = {Weber, Katrin and Bengio, Samy and Bourlard, Herv{\'{e}}},
       projects = {Idiap},
          title = {{HMM2}- {A} {N}ovel {A}pproach to {HMM} Emission {P}robability Estimation},
           type = {Idiap-RR},
         number = {Idiap-RR-30-2000},
           year = {2000},
    institution = {IDIAP},
        address = {Martigny, Switzerland},
           note = {Published: ICSLP 2000, Beijing, October 2000},
       abstract = {In this paper, we discuss and investigate a new method to estimate local emission probabilities in the framework of hidden Markov models (HMM). Each feature vector is considered to be a sequence and is supposed to be modeled by yet another HMM. Therefore, we call this approach `HMM2'. There is a variety of possible topologies of such HMM2 systems, e.g. incorporating trellis or ergodic HMM structures. Preliminary HMM2 speech recognition experiments on cepstral and spectral features yielded worse results than state-of-the-art systems. However, we believe that HMM2 systems have a lot of potential advantages and are therefore worth investigating further.},
            pdf = {https://publications.idiap.ch/attachments/reports/2000/rr00-30.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2000/rr00-30.ps.gz},
ipdinar={2000},
ipdmembership={speech},
language={English},
}