Abstract
Pathological vocal folds are known to exhibit multiple oscillation patterns, depending on tissue imbalance, subglottal pressure level, and other factors. This includes mid-phonation changes due to bifurcations in the underlying voice source system. Knowledge of when changes in oscillation patterns occur is helpful in the assessments of voice disorders, and the knowledge could be transformed into useful objective measures. Mid-phonation bifurcations can occur in rapid succession; hence, a fast classification of oscillation pattern is critical to minimize the averaging of data across bifurcations. This paper proposes frequency-ratio based short-term measures, named harmonic disturbance factor (HDF) and biphonic index (BI), towards the detection of the bifurcations. For the evaluation of HDF and BI, a frequency selection algorithm for glottal source signals is devised, and its efficacy is demonstrated with the glottal area waveforms of four cases, representing the wide range of oscillatory behaviors. The HDF and BI exhibit clear transitions when the voice bifurcations are apparent in the spectrograms. The presented proof-of-concept experiment’s outcomes warrant a larger scale study to formalize the parameters of the frequency selection algorithm.
Highlights
Normal healthy voice exhibits a nearly periodic behavior, which can be readily observed in its acoustic or glottal source signals via spectral visualization techniques such as spectrogram, power spectrum, or cepstrogram
The pathological interference of vocal fold oscillation leads to an anomaly in voice signals
biphonia index (BI) short-term parameters for the glottal area waveforms obtained from high-speed videoendoscopy data
Summary
Normal healthy voice exhibits a nearly periodic behavior, which can be readily observed in its acoustic or glottal source signals via spectral visualization techniques such as spectrogram, power spectrum, or cepstrogram. Often introduces interference to the vibration of vocal folds, forcing them to oscillate without collision or out of sync or sometimes even chaotically [1,2]. Such disruptions directly translate to a loss of voice quality, often described as hoarse, rough, breathy, or strained. Type I—nearly periodic; Type II—contain intermittency, strong subharmonics, or modulations; and. These types are used throughout the paper. Classification of these types were suggested to be done via visual inspection of the spectrogram of the voice signal under study
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