%Aigaion2 BibTeX export from Idiap Publications
%Friday 05 December 2025 01:08:24 PM

@INPROCEEDINGS{hynek-rr-03-50b,
                      author = {Hermansky, Hynek},
                    projects = {Idiap},
                       title = {{TRAP-TANDEM:} {D}ata-driven extraction of temporal features from speech},
                   booktitle = {large part published in Proceedings of ASRU-2003},
                      number = {50},
                        year = {2003},
                 institution = {IDIAP},
                     address = {Martigny, Switzerland},
                        note = {IDIAP-RR 03-50},
                    crossref = {hynek-rr-03-50},
                    abstract = {Conventional features in automatic recognition of speech describe instantaneous shape of a short-time spectrum of speech. The TRAP-TANDEM features describe likelihoods of sub-word classess at a given time instant, derived from temporal trajectories of band-limited spectral densities in the vicinity of a given time instant. The paper presents some rationale behind the data-driven TRAP-TANDEM approach, briefly describes the technique, point to relevant oublications and summarizes results achieved so far.},
                         pdf = {https://publications.idiap.ch/attachments/reports/2003/rr03-50.pdf},
                  postscript = {ftp://ftp.idiap.ch/pub/reports/2003/rr03-50.ps.gz},
ipdinar={2003},
ipdmembership={speech},
language={English},
}



crossreferenced publications: 
@TECHREPORT{hynek-rr-03-50,
                      author = {Hermansky, Hynek},
                    projects = {Idiap},
                       title = {{TRAP-TANDEM:} {D}ata-driven extraction of temporal features from speech},
                        type = {Idiap-RR},
                      number = {Idiap-RR-50-2003},
                        year = {2003},
                 institution = {IDIAP},
                     address = {Martigny, Switzerland},
                        note = {large part published in Proceedings of ASRU-2003},
                    abstract = {Conventional features in automatic recognition of speech describe instantaneous shape of a short-time spectrum of speech. The TRAP-TANDEM features describe likelihoods of sub-word classess at a given time instant, derived from temporal trajectories of band-limited spectral densities in the vicinity of a given time instant. The paper presents some rationale behind the data-driven TRAP-TANDEM approach, briefly describes the technique, point to relevant oublications and summarizes results achieved so far.},
                         pdf = {https://publications.idiap.ch/attachments/reports/2003/rr03-50.pdf},
                  postscript = {ftp://ftp.idiap.ch/pub/reports/2003/rr03-50.ps.gz},
ipdinar={2003},
ipdmembership={speech},
language={English},
}