%Aigaion2 BibTeX export from Idiap Publications
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@TECHREPORT{valente:rr08-12,
                      author = {Valente, Fabio and Hermansky, Hynek},
                    projects = {Idiap},
                       title = {On the Combination of Auditory and Modulation Frequency Channels for ASR applications},
                        type = {Idiap-RR},
                      number = {Idiap-RR-12-2008},
                        year = {2008},
                 institution = {IDIAP},
                        note = {Published in Interspeech 2008},
                    abstract = {This paper investigates the combination of evidence coming from different frequency channels obtained filtering the speech signal at different auditory and modulation frequencies. In our previous work \cite{icassp2008}, we showed that combination of classifiers trained on different ranges of {\it modulation} frequencies is more effective if performed in sequential (hierarchical) fashion. In this work we verify that combination of classifiers trained on different ranges of {\it auditory} frequencies is more effective if performed in parallel fashion. Furthermore we propose an architecture based on neural networks for combining evidence coming from different auditory-modulation frequency sub-bands that takes advantages of previous findings. This reduces the final WER by 6.2\\% (from 45.8\\% to 39.6\\%) w.r.t the single classifier approach in a LVCSR task.},
                         pdf = {https://publications.idiap.ch/attachments/reports/2008/valente-idiap-rr-08-12.pdf},
                  postscript = {ftp://ftp.idiap.ch/pub/reports/2008/valente-idiap-rr-08-12.ps.gz},
ipdmembership={speech},
}