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% Function to estimate glottal closure instants (GCIs) using an extension
% of Thomas Drugman's SEDREAMS algorithm, optimised to better handle
% non-modal phonation types
% Octave compatible
% Description
% Function to extract GCIs using an adapted version of the SEDREAMS
% algorithm which is optimised for non-modal voice qualities. Ncand maximum
% peaks are selected from the LP-residual signal in the interval defined by
% the mean-based signal. A dynamic programming algorithm is then used to
% select the optimal path of GCI locations. Then a post-processing method,
% using the output of a resonator applied to the residual signal, is
% carried out to remove false positives occurring in creaky speech regions
% Inputs
% x : [samples] [Nx1] Speech signal
% fs : [Hz] [1x1] sampling frequency
% F0mean : [Hz] [1x1] Mean fundamental frequency
% creak : [binary] [Nx1] Creak decision (OPTIONAL)
% Outputs
% GCI : [s] [Mx1] Glottal closure instants
% Example
% GCI = se_vq(x,fs);
% References
% [1] Kane, J., Gobl, C., (2013) `Evaluation of glottal closure instant
% detection in a range of voice qualities', Speech Communication
% 55(2), pp. 295-314.
% Copyright (c) 2013 Trinity College Dublin
% License
% This code is a part of the Voice Analysis Toolkit with the following
% licence:
% The software product (and any modifications thereof) is distributed under
% a dual licence: an open source license for individual, non-commercial
% purposes, and a commercial license. The opensource licence under which
% the product is distributed is GNU GPL v2. For individual users, this
% licence suits their use as these are not distributing proprietary
% modifications, additions to, or derivatives of the product and don't
% require legal protection of a commercial licence. For commercial users,
% where open source does not meet their requirements, we offer commercial
% licensing of the product. A commercial license permits customers to
% modify, add or produce derivative products without the obligation of
% making the subsequent code open source. For more information regarding
% our commercial licence, please contact
% This function is part of the Covarep project:
% Author
% John Kane
function GCI = se_vq(x,fs,F0mean,creak)
%% Settings
T0mean = fs/F0mean; % Rough period length for mean-based signal
winLen = 25; % window length in ms
winShift = 5; % window shift in ms
LPC_ord = round(fs/1000)+2; % LPC order
Ncand=5; % Number of candidate GCI residual peaks to be considered in the dynamic programming
trans_wgt=1; % Transition cost weight
relAmp_wgt=0.3; % Local cost weight
removeThresh=0.4; % Threshold for removing false GCIs
%% Calculate LP-residual and extract N maxima per mean-based signal determined intervals
res = lpcresidual(x,winLen/1000*fs,winShift/1000*fs,LPC_ord); % Get LP residual
rep = RCVD_reson_GCI(res,fs,F0mean); % Get resonator output
MBS = get_MBS(x,fs,T0mean); % Extract mean based signal
interval = get_MBS_GCI_intervals(MBS,fs,T0mean,F0max); % Define search intervals
[GCI_N,GCI_relAmp] = search_res_interval_peaks(res,interval,Ncand); % Find residual peaks
GCI = RESON_dyProg_mat(GCI_relAmp',GCI_N',F0mean,x,fs,trans_wgt,relAmp_wgt); % Do dynamic programming
%% Remove false alarms as weak peaks in resonator output
if nargin > 3
GCI = GCI_creak_postproc(GCI,creak,search_reg,rep,removeThresh,repNum);
GCI = (GCI-1)/fs;