DocumentCode :
177753
Title :
Subband analysis of linear prediction residual for the estimation of glottal closure instants
Author :
Vikram, R.L. ; Vijay Girish, K.V. ; Harshavardhan, S. ; Ramakrishnan, A.G. ; Ananthapadmanabha, T.V.
Author_Institution :
Victoria Univ. of Wellington, Wellington, New Zealand
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
945
Lastpage :
949
Abstract :
Many state-of-the-art techniques for estimating glottal closure instants (GCIs) use linear prediction residual (LPR) in one way or another. In this paper, subband analysis of LPR is proposed to estimate the GCIs. A composite signal is derived as the sum of the envelopes of the subband components of the LPR signal. Appropriately chosen peaks of the composite signal are the GCI candidates. The temporal locations of the candidates are refined using the LPR to obtain the GCIs, which are validated against the GCIs obtained from the electroglot-tograph signal, recorded simultaneously. The robustness is studied using additive white, babble and vehicle noises for different signal to noise ratios. The proposed method is evaluated using six different databases and compared with three state-of-the-art LPR based methods. The results show that the performance of the proposed method is comparable to the best of the LPR based techniques for clean as well as noisy speech.
Keywords :
channel bank filters; speech processing; speech synthesis; white noise; GCI; LPR signal; additive white noise; babble noise; composite signal; electroglottograph signal; glottal closure instants; linear prediction residual; noisy speech; subband analysis; vehicle noise; Accuracy; Databases; Estimation; Signal to noise ratio; Speech; Vehicles; GCI; HBE; HBEBEST; Hamming filter; LPR; composite signal; glottal closure instant; subbands;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6853736
Filename :
6853736
Link To Document :
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