Comparison of an audio-based and a video-based approach for detecting diplophonia

Aichinger, Philipp; Roesner, Imme; Leonhard, Matthias; Schneider‐Stickler, Berit; Denk-Linnert, Doris-Maria; Bigenzahn, Wolfgang; Fuchs, Anna; Hagmüller, Martín; Kubin, Gernot

doi:10.1016/j.bspc.2014.10.001

Cited by 8 publications

(3 citation statements)

References 24 publications

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“…Also, the obtained imaging data might be of low temporal and spatial resolution, and the methods do not enable a noninvasive analysis of voice production. Laryngeal imaging has been used jointly with acoustical analysis of speech excitation information in studying, for example, glottic cancer [53], diplophonia [54], and phonation onsets [55]. For visualization, simultaneously recorded HSV and EGG signals are shown in Fig.…”

Section: E X T R a C T I O N O F E X C I T A T I O N I N F O R M A T I O N U S I N G N O N A C O U S T I C A L T E C H N I Q U E Smentioning

confidence: 99%

Extraction and Utilization of Excitation Information of Speech: A Review

2021

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| Speech production can be regarded as a process where a time-varying vocal tract system (filter) is excited by a time-varying excitation. In addition to its linguistic message, the speech signal also carries information about, for example, the gender and age of the speaker. Moreover, the speech signal includes acoustical cues about several speaker traits, such as the emotional state and the state of health of the speaker. In order to understand the production of these acoustical cues by the human speech production mechanism and utilize this information in speech technology, it is necessary to extract features describing both the excitation and the filter of the human speech production mechanism. While the methods to estimate and parameterize the vocal tract system are well established, the excitation appears less studied. This article provides a review of signal processing approaches used for the extraction of excitation information from speech. This article highlights the importance of excitation information in the analysis and classification of phonation type and vocal emotions, in the analysis of nonverbal laughter sounds, and in studying pathological voices. Furthermore, recent developments of deep learning techniques in the context of extraction and utilization of the excitation information are discussed.

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Section: E X T R a C T I O N O F E X C I T A T I O N I N F O R M A T I O N U S I N G N O N A C O U S T I C A L T E C H N I Q U E Smentioning

confidence: 99%

Extraction and Utilization of Excitation Information of Speech: A Review

2021

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“…Although recent research emphasis is on developing fully automated segmentation to extract the glottal area from HSV image sequences, semi-automatic methods remain widely used. For example, the adapted seeded region growing algorithm developed by Lohscheller et al (2007), which uses manually picked seed points, and a spatially and temporally varying threshold as the region membership criterion, has been used by, for example, Aichinger et al (2017), Döllinger et al (2017), and Patel et al (2017a), and included in HSV data analysis toolkits such as GlottalImageExplorer (Birkholz, 2016).…”

Section: Laryngostroboscopy and Videokymographymentioning

confidence: 99%

Interaction Mechanisms between Glottal Source and Vocal Tract in Pitch Glides

Murtola¹,

Malinen²

2018

Interspeech 2018

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“…In contrast, pressedness was found to be associated with decreases of leftright and anterior-posterior phase differences [14], decreased open quotients [7,10,8], completeness of glottal closure [5], a decreased ratio of cyclic GAW minima to maxima [15], with GAW cycle shape [16], with decreased "zipperlikeness" [13], as well as with phonatory onset latency and speed of adduction [5]. Diplophonia was found to be related to irregular glottal closure and periodicity differences [2], frequency bimodality of vocal fold vibration [17], a repetitive pattern of glottal closures [18], bicyclicity [19], as well as with metacycycles, phase differences, and closure incompleteness [20]. Fry was found to be related to metacycles, i.e., with 2 or 3 pulses followed by a long closed phase [2], or 2 small openings and closings of the vocal folds in rapid succession followed by a relatively long closed phase [20].…”

Section: Introductionmentioning

confidence: 99%

Aerodynamics and Lumped-Masses Combined with Delay Lines for Modeling Vertical and Anterior-Posterior Phase Differences in Pathological Vocal Fold Vibration

Drioli

Aichinger

2019

Interspeech 2019

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We discuss the representation of anterior-posterior (A-P) phase differences in vocal cord oscillations through a numerical biomechanical model involving lumped elements as well as distributed elements, i.e., delay lines. A dynamic glottal source model is illustrated in which the fold displacement along the vertical and the longitudinal dimensions is explicitly modeled by numerical waveguide components representing the propagation on the fold cover tissue. In contrast to other models of the same class, in which the reproduction of longitudinal phase differences are intrinsically impossible (e.g., in two-mass models) or not easy to control explicitely (e.g., in 3D 16-mass and multi-mass models in general), the one proposed here provides direct control over the amount of phase delay between folds oscillations at the posterior and anterior side of the glottis, while keeping the dynamic model simple and computationally efficient. The model is assessed by addressing the reproduction of typical oscillatory patterns observed in high-speed videoendoscopic data, in which A-P phase differences are observed. Experimental results are provided which demonstrate the ability of the approach to effectively reproduce different oscillatory patterns of the vocal folds.

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Comparison of an audio-based and a video-based approach for detecting diplophonia

Cited by 8 publications

References 24 publications

Extraction and Utilization of Excitation Information of Speech: A Review

Extraction and Utilization of Excitation Information of Speech: A Review

Interaction Mechanisms between Glottal Source and Vocal Tract in Pitch Glides

Aerodynamics and Lumped-Masses Combined with Delay Lines for Modeling Vertical and Anterior-Posterior Phase Differences in Pathological Vocal Fold Vibration

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