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Detail of publication


Legát, M. and Matoušek, J. and Tihelka, D. : On the detection of pitch marks using a robust multi-phase algorithm . Speech Communication, p. 552-566, Elsevier, 2011.

Additional information



A large number of methods for identifying glottal closure instants (GCIs) in voiced speech have been proposed in recent years. In this paper, we propose to take advantage of both glottal and speech signals in order to increase the accuracy of detection of GCIs. All aspects of this particular issue, from determining speech polarity to handling a delay between glottal and corresponding speech signal, are addressed. A robust multi-phase algorithm (MPA), which combines different methods applied on both signals in a unique way, is presented. Within the process, a special attention is paid to determination of speech waveform polarity, as it was found to be considerably influencing the performance of the detection algorithms. Another feature of the proposed method is that every detected GCI is given a confidence score, which allows to locate potentially inaccurate GCI subsequences. The performance of the proposed algorithm was tested and compared with other freely available GCI detection algorithms. The MPA algorithm was found to be more robust in terms of detection accuracy over various sets of sentences, languages and phone classes. Finally, some pitfalls of the GCI detection are discussed.

Detail of publication

Title: On the detection of pitch marks using a robust multi-phase algorithm
Author: Legát, M. ; Matoušek, J. ; Tihelka, D.
Language: English
Date of publication: 21 Jan 2011
Year: 2011
Type of publication: Papers in journals
Title of journal or book: Speech Communication
Page: 552 - 566
ISSN: 0167-6393
Publisher: Elsevier
/ 2013-03-21 09:07:56 /


glottal closure instant, pitch mark, speech signal polarity, fundamental frequency


 author = {Leg\'{a}t, M. and Matou\v{s}ek, J. and Tihelka, D.},
 title = {On the detection of pitch marks using a robust multi-phase algorithm},
 year = {2011},
 publisher = {Elsevier},
 journal = {Speech Communication},
 pages = {552-566},
 ISSN = {0167-6393},
 url = {},