@InProceedings{Supelec452,
author = {Stéphane Rossignol and Olivier Pietquin},
title = {{Precise Voicing Information Extraction in Speech Signals Using the Analytic Signal}},
year = {2008},
booktitle = {{Proceedings of the 8th IEEE Symposium on Signal Processing and Information Technology (ISSPIT 2008)}},
pages = {207-212},
month = {December},
address = {Sarajevo (Bosnia \& Herzegovina)},
url = {http://www.metz.supelec.fr/metz/personnel/pietquin/pdf/ISSPIT_2008_OPSR.pdf},
doi = {10.1109/ISSPIT.2008.4775673},
abstract = {This paper proposes a voiced – unvoiced measure based on the
Analytic Signal computation. This voiced – unvoiced feature can
be useful for many speech processing applications. For
instance, considering speech recognition, it could be
incorporated into commonly used acoustic feature vectors, such
as for example the Mel Frequency Cepstral Coefficients (MFCC)
and their first two derivatives, in order to improve the
performance of the overall system. The evaluation of the
developed measure has been performed on the TIMIT database.
TIMIT has been manually segmented into phones. The voicing
information can easily be derived from this segmentation.
It is shown in this paper that the automatic voiced – unvoiced
segmentation obtained using the method described in the next
sections and the manual voiced – unvoiced segmentation provided
by TIMIT are very similar.}
}