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Glottal Closure Instants (GCIs) are referred to the instances of significant excitation of the vocal tract.

I have seen in some papers that I can measure instant of glottal closure in a voiced segment directly from speech waveforms.

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Can someone provide me information how detect GCIs ?

How Glottal Closure Instants can be estimated ?

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  • $\begingroup$ Not clear.. are you having difficulty in understanding some paper? $\endgroup$ – user13107 Aug 5 '13 at 6:39
  • $\begingroup$ How Glottal Closure Instants can be estimated ? $\endgroup$ – ederwander Aug 5 '13 at 12:35
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There are many ways to estimate the instant of glottal closure (GCI). Here (PDF link) is a recent journal article that reviews many of them. The freely-available VOICEBOX toolbox for Matlab includes a couple GCI estimation techniques.

For most approaches, the fundamental idea is the same: the speech signal is can be viewed as an excitation signal resonating an all-pole filter, and the location of the excitation instants is the instant of glottal closure.

A simple GCI estimation algorithm might work like this. The all-pole filter (encapsulating the contributions of the vocal tract and glottal source) can be estimated using linear prediction. Inverse filtering the speech signal with this (time-varying) filter will give the linear predictive residual signal, which is an estimate of the excitation signal. For normal voices, this signal will look like a noise impulse train. Peak-picking this signal will give good results for these voices during sustained vowels. Voice offsets and onsets will be more troublesome, as well as voices that are very breathy or irregular.

(A quick note about your figure: the signal marked as the residual seems to include glottal source signal, and so it not a linear prediction residual in the same sense as what I refer to in the above.)

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As others have mentioned, there have been many methods developed to determine voicing of speech and, for voiced speech, to mark the individual pitch epochs. This is not a trivial problem if one wants to have robust and accurate epoch marking. There are many challenges, diplophonic speech is one of them. Both time-domain as well as frequency-domain techniques exist. In this paper you can find description of five techniques (detailed enough to enable you to implement them), their comparison, and a set of intuitive enhancements -- a great starting point if you want to develop your own algorithm. If you need high-quality speech processing (e.g. to minimize any jitter) then I strongly recommend this paper. It describes the essence of a very accurate and reliable method but be prepared to do a lot of detailed development yourself.

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The following paper gives an insight on avoiding dependence on GCI for speech processing http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6952839&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6952839

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