Glottal inverse filtering analysis of human voice production — A review of estimation and parameterization methods of the glottal excitation and their applications-Reference-Cited by-同舟云学术

Glottal inverse filtering analysis of human voice production — A review of estimation and parameterization methods of the glottal excitation and their applications

Published:2011-10 Issue:5 Volume:36 Page:623-650
ISSN:0256-2499
Container-title:Sadhana
language:en
Short-container-title:Sadhana

Author:

ALKU PAAVO

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://link.springer.com/content/pdf/10.1007/s12046-011-0041-5.pdf

Reference213 articles.

1. Airas M 2008 TKK Aparat: An environment for voice inverse filtering and parameterization, Logoped. Phoniatr. Vocol. 33: 49–64

2. Airas M, Alku P 2006 Emotions in vowel segments of continuous speech, Phonetica 63: 26–46

3. Airas M, Alku P, Vainio M 2007 Laryngeal voice quality changes in expression of prominence in continuous speech. Proc. 5th Int. Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA’07), 135–138

4. Akande O, Murphy P 2005 Estimation of the vocal tract transfer function with application to glottal wave analysis, Speech Commun. 46: 15–36

5. Alku P 1992 Glottal wave analysis with pitch synchronous iterative adaptive inverse filtering, Speech Commun. 11(2–3): 109–118

Cited by 127 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Continuous-time model identification of the subglottal system;Biomedical Signal Processing and Control;2024-09

2. Classification of phonation types in singing voice using wavelet scattering network-based features;JASA Express Letters;2024-06-01

3. Symmetric and asymmetric Gaussian weighted linear prediction for voice inverse filtering;Speech Communication;2024-04

4. The Physics of the Human Vocal Folds as a Biological Oscillator;New Insights on Oscillators and Their Applications to Engineering and Science;2024-03-20

5. Investigation of self-supervised pre-trained models for classification of voice quality from speech and neck surface accelerometer signals;Computer Speech & Language;2024-01