Identification of glottal instants using electroglottographic signal for vulnerable cases of voicing

• Main Authors: Tanumay Mandal, Krothapalli Sreenivasa Rao, Sanjay K. Gupta
• Format: Article
• Language: English
• Published: Wiley 2020-11-01
• Series: Healthcare Technology Letters
• Subjects: feature extraction; medical signal processing; medical signal detection; speech recognition; pathological egg signal; electroglottographic signal; glottal instant identification; instant detection methods; biomedical applications; glottal closing; glottal opening; phase information
• Online Access: https://digital-library.theiet.org/content/journals/10.1049/htl.2019.0085

Robust detection of glottal instants is essential for various speech and biomedical applications. Glottal closing and glottal opening are two crucial instants/epochs of a glottal cycle. The first-order derivative of the Electroglottographic (EGG) signal demonstrates important peaks at those locations for standard voicing, but the detection of glottal instants becomes erroneous when the peak to peak amplitude of the EGG signal is very low, irregular and unpredictable. In this work, a new efficient method is proposed for identification of glottal instants from the EGG signals including the segments of the signals where the signals are feeble with irregular periodicity. The overall accuracy of detection will be enhanced by identifying the glottal instants for the whole part of the signal including the vulnerable segments of signal. As the phase of a signal is uniform in nature, the phase information of the EGG signal has been explored to detect glottal instants accurately. Under low strength of the EGG signal, the proposed method remarkably has better performance compared to the existing instants detection methods and for pathological EGG signal, the detection accuracy of glottal instants is better than other existing methods.