%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{Parthasarathi_TSD2008_2008,
                      author = {Parthasarathi, Sree Hari Krishnan and Motlicek, Petr and Hermansky, Hynek},
                    projects = {Idiap},
                       month = {9},
                       title = {Exploiting Contextual Information for Speech/Non-Speech Detection},
                   booktitle = {Text, Speech and Dialogue},
                      series = {Series of Lecture Notes In Artificial Intelligence (LNAI)},
                      volume = {5246},
                        year = {2008},
                   publisher = {Springer-Verlag  Berlin, Heidelberg},
                    location = {Brno, Czech Republic},
                        isbn = {978-3-540-87390-7},
                    crossref = {parthasarathi:rr08-22},
                    abstract = {In this paper, we investigate the effect of temporal context for speech/non-speech detection (SND). It is shown that even a simple feature such as full-band energy, when employed with a large-enough context, shows promise for further investigation. Experimental evaluations on the test data set, with a state-of-the-art multi-layer perceptron based SND system and a simple energy threshold based SND method, using the F-measure, show an absolute performance gain of 4.4\% and 5.4\% respectively. The optimal contextual length was found to be 1000 ms. Further numerical optimizations yield an improvement (3.37\% absolute,',','),
 resulting in an absolute gain of 7.77\% and 8.77\% over the MLP based and energy based methods respectively. ROC based performance evaluation also reveals promising performance for the proposed method, particularly in low SNR conditions.},
                         pdf = {https://publications.idiap.ch/attachments/papers/2008/Parthasarathi_TSD2008_2008.pdf}
}



crossreferenced publications: 
@TECHREPORT{parthasarathi:rr08-22,
                      author = {Parthasarathi, Sree Hari Krishnan and Hermansky, Hynek},
                    projects = {Idiap},
                       title = {Exploiting contextual information for speech/non-speech detection},
                        type = {Idiap-RR},
                      number = {Idiap-RR-22-2008},
                        year = {2008},
                 institution = {IDIAP},
                    abstract = {In this paper, we investigate the effect of temporal context for speech/non-speech detection (SND). It is shown that even a simple feature such as full-band energy, when employed with a large-enough context, shows promise for further investigation. Experimental evaluations on the test data set, with a state-of-the-art multi-layer perceptron based SND system and a simple energy threshold based SND method, using the F-measure, show an absolute performance gain of $4.4\%$ and $5.4\%$ respectively. The optimal contextual length was found to be 1000 ms. Further numerical optimizations yield an improvement ($3.37\%$ absolute,',','),
 resulting in an absolute gain of $7.77\%$ and $8.77\%$ over the MLP based and energy based methods respectively. ROC based performance evaluation also reveals promising performance for the proposed method, particularly in low SNR conditions.},
                         pdf = {https://publications.idiap.ch/attachments/reports/2008/parthasarathi-idiap-rr-08-22.pdf},
                  postscript = {ftp://ftp.idiap.ch/pub/reports/2008/parthasarathi-idiap-rr-08-22.ps.gz},
ipdmembership={speech},
}